Algorithm Engineer jobs in Israel

Istra is a leading Algo-Trading research company specializing in developing and deploying High Frequency Trading strategies (HFT). We use state of the art technology and algorithms that are developed by our elite highly-skilled group of experienced researchers and developers in a challenging, pleasant, and rewarding work environment. We are looking for outstanding Algorithms Developers to join our team. In this role, you will do: End to end development and deployment of high frequency trading algorithms. Development and application of trading algos in a highly competitive real time environment. Analyzing large and complex data sets finding ways to improve existing trading strategies. Building scalable infrastructures and developing algorithms for modeling the financial market. Requirements What you'll need to succeed: Cum laude BSc. in Mathematics, Physics, Computer Science or Electrical Engineering from a well-known academic institute At least 3 years of industry experience Strong programming skills, preferably in C/C++/R. Strong statistical, mathematical and problem-solving skills- advantage Self-motivation and ability to communicate within and across teams A deep sense of intellectual curiosity and excellence Independent, thorough, motivated and innovative So, if you love challenges, have a constant striving for excellence and enjoy a high level of autonomy and independence, we would love to hear from you.

REAL is building an AI Execution Platform for real estate organizations. Today, the data required to run real estate is scattered across PDFs, spreadsheets, emails, drawings, public records, and disconnected systems, leading to preventable leakage, missed obligations and lost opportunities to improve performance. Used by leading enterprises, REAL converts this fragmented data into connected intelligence and automated action. With advanced AI, universal ingestion, and modular execution agents, REAL increases operational accuracy, uncovers financial discrepancies, and surfaces opportunities to optimize performance and enhance business outcomes. REAL Values Ownership: We take responsibility and move decisively. Clarity: We simplify complexity to deliver meaningful impact. Accuracy: Precision matters, in our product and in how we operate. Velocity: We work with urgency and intent. Partnership: We collaborate closely with our customers and with each other. Role Overview As an AI Algorithm Engineer at REAL, you’ll design and implement advanced algorithmic workflows that power our data digestion pipelines and conversational AI agent experience. You will: • Architect and build workflows that turn raw, unstructured data (e.g., PDF documents and ultra high-resolution architectural drawings) into meaningful, structured context for downstream analysis. • Combine techniques from classical NLP, computer vision, unsupervised learning, and graph theory to build robust end-to-end pipelines - not just standard LLM API calls, but intelligent decomposition, structuring, and context engineering. • Develop AI agent workflows that let customers explore, query, and reason about their data naturally and reliably. • Build strong evaluation infrastructure to benchmark and continuously improve both classical algorithmic components and LLM-based workflows. • Work primarily in Python, and collaborate across systems and services in TypeScript when needed. • Move fast from prototype to production, while maintaining correctness, scalability, and measurable quality. Requirements What You’ll Do Core Responsibilities • Design and implement end-to-end data digestion pipelines for complex unstructured and semi-structured inputs. • Integrate classical algorithms with LLM-centric workflows to produce high-quality contextual inputs for reasoning tasks. • Build systems for segmentation, structure extraction, semantic decomposition, embedding-based representations, and graph construction. • Develop agentic workflows that combine tools, retrieval, and reasoning for interactive customer experiences. • Design evaluation suites, datasets, metrics, and regression tests to measure quality, robustness, and performance over time. • Continuously refine workflows based on customer usage, failure analysis, and measurable improvements. What We're Looking For Required Qualifications • MSc (or equivalent experience) in Computer Science, Mathematics, Electrical Engineering, or a related quantitative field. • 5+ years of experience in data science / algorithm development / applied research engineering roles. • Strong experience building complex algorithmic workflows beyond model calls - including multi-stage pipelines, feature extraction, structure inference, and optimization. • Deep understanding of LLM digestion concepts: RAG, context engineering, chunking strategies, retrieval and ranking, tool usage patterns, and reliability techniques. • Experience designing and maintaining evaluation frameworks for both classical algorithms and LLM workflows (offline + online, regression, benchmarking). • Strong programming skills in Python; familiarity with TypeScript is a plus. • Ability to thrive in a high-ownership startup environment: ambiguity, speed, responsibility, and continuous learning. Nice To Have • Familiarity with vector databases and scalable retrieval architectures. • Familiarity with agent orchestration frameworks (e.g., LangChain) and tool-driven reasoning systems. • Experience deploying AI workflows into production with monitoring, guardrails, and iteration loops. Benefits Why Join REAL • You’ll work on problems that don’t have a pre-scripted solution - it’s a privilege to be among the first to tackle them. • High ownership and direct impact on the core product and architecture. • A fast iteration environment where strong engineers ship meaningful work quickly. • A chance to grow alongside the AI revolution - adapting, learning, and building what’s next.

Description Senior Algorithms Engineer – Estimation & Navigation Full-time | R&D About Us Smart Shooter is looking for an experienced Mechanical Engineer with strong capabilities in mechanical and opto-mechanical design for leading development projects, product design, and working in a multi-program, highly multidisciplinary environment. The Role We are looking for an experienced algorithms engineer to join our R&D team and take a leading role in developing navigation, estimation and data-fusion algorithms. • Develop and validate navigation and estimation algorithms • Design statistical data-fusion solutions that combine multiple sources • Model, simulate and analyze algorithm performance • Work closely with multidisciplinary engineering teams Requirements • B.Sc. or M.Sc. in Electrical, Aerospace or Mechanical Engineering, Physics, or a related field • At least 4–7 years of hands-on experience developing algorithms • Strong background in navigation algorithms and estimation theory, including the Kalman filter family • Experience with statistical multi-source data fusion • Proficiency in MATLAB and/or Python • Analytical, independent, and a strong team player Advantages • GNC experience • M.Sc. or Ph.D. in a relevant • Real-time / embedded implementation experience

Description Kela is a secure, open platform enabling rapid and seamless integration of commercial and military systems in service of Western defense. Designed and battle-tested by Israeli innovators, Kela ensures the West meets today's frontline challenges and evolves with tomorrow's innovations. Backed by leading investors, Kela combines Israeli innovation with global mission impact. About the Role Our Robotics department works across unmanned ground vehicles, humanoids, quadrupeds, and drones. We combine classical, modular policy stacks with modern physical AI — integrating and fine-tuning open-source foundation models, and designing and training our own perception, planning, and control modules where nothing off-the-shelf is good enough. We're looking for a world-class Senior Algorithm Developer to join the team. We need people who think big, move fast, and have a track record that proves they can take an algorithmic problem from a whiteboard sketch to a system running reliably in the field. Requirements Responsibilities • Research and develop algorithms spanning classical methods and deep learning. • Design and build perception, planning, localization, navigation and control modules for real, unstructured environments. • Integrate, adapt, and fine-tune open-source physical AI foundation models. • Own algorithmic pipelines end to end: data, simulation, training, evaluation, deployment. • Apply reinforcement learning and imitation learning to build robust, capable policies. • Build and run simulation environments to train and validate policies before field deployment. • Work closely with systems and software engineers to close the loop between algorithms and real-world performance. • Take ownership of problems end to end, from open question to fielded solution. Must-have • A proven track record of excellence — top academic background, competitive achievements, elite technological unit service, or high-impact work in industry — and the potential to become one of the strongest in the world in physical AI. • Several years of hands-on experience as an algorithm developer, with real seniority: someone who can own hard problems independently. • Strong foundations in classical algorithms and control, alongside real depth in modern deep learning. • A builder's mindset: comfortable with ambiguity, driven by hard problems, focused on real-world performance. • B.Sc./M.Sc./Ph.D. in Computer Science, Electrical Engineering, Robotics, Applied Math, Physics, or a related field from a leading institution. Nice-to-have • Hands-on experience with reinforcement learning and/or imitation learning. • Practical experience building data pipelines and simulation environments for training and evaluation. • Strong software engineering skills. • Experience integrating, fine-tuning, or deploying open-source foundation models. • Experience with robotics tooling (ROS/ROS2), simulators (Isaac Sim, Gazebo, MuJoCo), and deep learning frameworks (PyTorch, etc.). Why Join • Work across UGVs, humanoids, quadrupeds, and drones as the group grows. • Sit at the frontier of physical AI — shaping which approach wins for each problem, classical, learned, or hybrid. • Join a small, high-caliber team where your algorithms reach real robots in the field, fast. • Be part of a fast-growing, well-backed Israeli defense tech company with global impact.

Description What we are looking for: Nova is looking for an Algorithm Developer to join the DMD Advanced Technology team and help develop advanced imaging and image-analysis technologies. In this role, you will turn complex imaging data into robust algorithms, combining image processing, computer vision, and acceleration on graphics processing units (GPUs). You will work alongside software, systems, experimental physics, optics, hardware, and applications specialists. You will contribute throughout the development cycle, from investigating imaging challenges and designing algorithms to experimental validation and system integration. Your work will balance algorithm accuracy, robustness, and the demands of high-throughput image processing. We value analytical thinking, sound engineering judgment, and effective AI-assisted development over familiarity with a specific language or library. Role Responsibilities What will you be doing: • Design and develop image-processing and computer-vision algorithms for calibration, geometric correction, registration, segmentation, and feature extraction. • Develop methods that combine images acquired under different illumination conditions while accounting for acquisition variability. • Profile and optimize CPU and GPU processing, memory usage, and data movement to support system throughput targets while preserving algorithm accuracy. • Design experiments and reproducible evaluations on real-world imaging data, quantifying accuracy, robustness, and the impact of imaging artifacts. • Use AI coding assistants to accelerate implementation, debugging, testing, and refactoring, taking responsibility for the correctness and maintainability of the delivered code. • Develop tested algorithm components and partner with software engineers on system integration, automated regression checks, and deployment. • Collaborate with systems, experimental physics, optics, hardware, and applications specialists to investigate imaging challenges and guide experiments. • Present findings, explain technical tradeoffs, and document algorithm behavior, validation results, and performance improvements. Requirements Must Have • A bachelor's degree or higher in Electrical Engineering, Computer Science, Physics, Applied Mathematics, or a related quantitative discipline. • Approximately three years of relevant algorithm-development experience, or a relevant PhD with substantial hands-on algorithm research. • Strong foundations in image processing, computer vision, and applied mathematics or statistics. • Hands-on experience implementing and validating algorithms on real-world imaging or measurement data. • Hands-on experience developing, profiling, and optimizing GPU-accelerated image-processing or numerical algorithms, with measured runtime or memory-efficiency improvements and correctness validation. Understanding of CPU-GPU data transfers, synchronization, and memory constraints. • Strong programming fundamentals and practical development experience in Python, C++, Rust, or a comparable language. • Practical experience with AI-assisted development using tools such as Codex, Claude Code, GitHub Copilot, or equivalents, with the ability to critically review, debug, test, and explain generated code. • Working proficiency with Git, including branches, pull requests, code reviews, and resolving merge conflicts. Advantages • Experience in industrial imaging or image-analysis systems is strongly preferred. Semiconductor metrology, imaging, inspection, or equipment-development experience is a major advantage. • Custom GPU kernel development using CUDA C++ or Triton is strongly preferred. • Experience with GPU profiling tools such as NVIDIA Nsight, asynchronous processing, or multi-GPU workloads. • Experience with performance-oriented C++ or Rust development, parallel computing, or optimization of high-resolution imaging pipelines. • Experience with Azure DevOps or equivalent platforms and continuous integration and delivery (CI/CD) pipelines, including automated algorithm regression tests and reproducible builds. • Understanding of imaging physics, sensor noise, illumination, and image calibration. • Experience with machine learning or deep learning for image analysis, segmentation, or feature extraction. That special something you bring in: • Analytical curiosity and methodical problem solving: you turn complex imaging questions into testable hypotheses and use evidence to guide decisions. • A hands-on approach and ownership: you learn independently, follow problems through to a validated solution, and communicate limitations openly. • Team spirit and clear communication: you work effectively across scientific and engineering disciplines and explain technical findings to different audiences. Get to know us better: Nova (NASDAQ: NVMI) is a global company and a leading provider of innovative metrology solutions for process control in semiconductor manufacturing. With a team of ~1200 people in three R&D centers and 27 field offices, we bring insights into the world’s most advanced industry. We leverage multiple technology fields such as physics, optics, chemistry, and algorithms to develop hardware and software solutions that measure almost every advanced computer chip built in the world. Nova dives deep into dimensions and layers at the atomic level to extract unique insights and provide our customers with crucial decision-making data, managing critical challenges by providing unique, differentiated solutions. Our outstanding people-focused and innovative culture means every person at Nova has the power to make an impact and significantly redefine what people can achieve through technology. Join us if you are A dreamer and brilliant high aimer who sees the impossible as the starting point and loves working in a multidisciplinary global team to create innovative breakthroughs. If you need assistance due to a disability, you may contact us at [email protected]

Description Fetcherr builds responsible AI that transforms market complexity into measurable profit growth. At the core of the company is the Market Model - a proprietary AI-powered model delivering accurate, granular demand predictions with 96% forecast accuracy and real-time decision intelligence for commercial teams. Built on a glass-box architecture, it uses market data - not personal data - with full transparency into logic and outcomes. First deployed in global aviation, the technology is industry-agnostic and scales across volatile markets. Fetcherr delivers a consistent average profit uplift of 7%, with corporate partners including Delta, Virgin Atlantic, WestJet, Viva, and Azul. We are seeking an experienced Algorithm Team Lead - Optimization to lead our data science and data engineering efforts and oversee a team of skilled data engineers. This role combines hands-on technical leadership and team management, with responsibilities that include building and scaling data infrastructure to power real-time pricing, large-scale data pipelines, and machine learning products. The Price Optimization (PO) team is where insights become decisions. We work with large-scale customer data and market predictions — like demand forecasts — to drive revenue management decisions that actually move the needle. At our core, we build and maintain the decision-making engine. That means designing the data pipelines that bring customer data in, and running it through an optimization engine that simulates the market — weighing competition, pricing constraints, inventory availability, predictive models, and each client's unique business policies — to generate the best possible price recommendations. As the final step before recommendations reach the client, quality, reliability, and attention to detail aren't just nice to have. They're everything. You will lead the team through architecture decisions, development, and deployment of mission-critical systems—while growing and mentoring a high-performing team. Responsibilities: • Manage a team of data scientists and data engineers responsible for building robust, scalable, and high-performance data pipelines and infrastructure. • Design, build, and maintain distributed data processing workflows (batch & streaming). • Drive best practices for data quality, validation, testing, and observability. • Own and evolve Fetcherr’s data architecture in alignment with business and product goals. • Manage sprint planning, task breakdown, code reviews, and performance feedback for your team. • Contribute hands-on to key development tasks and architecture decisions. • Recruit, mentor, and grow the data science engineering team. Requirements • Proven experience as a Data Scientist. • Proven experience designing and maintaining large-scale data platforms (hundreds of TBs) • 3+ years of proven experience leading and managing a team of data engineers (people management is required) • 4+ years of experience in data science, including a strong Python programming background, advanced SQL skills, and data modeling experience • Expertise with data orchestration tools (Airflow, Prefect, or Dagster) • Cloud platform experience — GCP preferred (AWS/Azure acceptable) • Familiarity with Docker • Strong communication, mentorship, and collaboration skills • BSc/MSc in Mathematics/ physics/ statistics/ Computer Science. • Fluent English (spoken and written) Nice to have: • Experience with Google Cloud Platform tools (BigQuery, Dataflow, Pub/Sub) • Background working with ML pipelines or data science teams • Understanding of data contracts, lineage, and versioning tools • Knowledge of data structures and algorithms • Experience optimizing pipelines and databases for performance and cost • CI/CD pipelines (GitHub/GitLab) • Hands-on experience with distributed data frameworks (Apache Beam, Spark, or similar) • Exposure to airline, pricing, or GDS systems

Description Fetcherr builds responsible AI that transforms market complexity into measurable profit growth. At the core of the company is the Market Model - a proprietary AI-powered model delivering accurate, granular demand predictions with 96% forecast accuracy and real-time decision intelligence for commercial teams. Built on a glass-box architecture, it uses market data - not personal data - with full transparency into logic and outcomes. First deployed in global aviation, the technology is industry-agnostic and scales across volatile markets. Fetcherr delivers a consistent average profit uplift of 7%, with corporate partners including Delta, Virgin Atlantic, WestJet, Viva, and Azul. We are seeking an experienced Algorithm Team Lead - Optimization to lead our data science and data engineering efforts and oversee a team of skilled data engineers. This role combines hands-on technical leadership and team management, with responsibilities that include building and scaling data infrastructure to power real-time pricing, large-scale data pipelines, and machine learning products. The Price Optimization (PO) team is where insights become decisions. We work with large-scale customer data and market predictions — like demand forecasts — to drive revenue management decisions that actually move the needle. At our core, we build and maintain the decision-making engine. That means designing the data pipelines that bring customer data in, and running it through an optimization engine that simulates the market — weighing competition, pricing constraints, inventory availability, predictive models, and each client's unique business policies — to generate the best possible price recommendations. As the final step before recommendations reach the client, quality, reliability, and attention to detail aren't just nice to have. They're everything. You will lead the team through architecture decisions, development, and deployment of mission-critical systems—while growing and mentoring a high-performing team. Responsibilities: • Manage a team of data scientists and data engineers responsible for building robust, scalable, and high-performance data pipelines and infrastructure. • Design, build, and maintain distributed data processing workflows (batch & streaming). • Drive best practices for data quality, validation, testing, and observability. • Own and evolve Fetcherr’s data architecture in alignment with business and product goals. • Manage sprint planning, task breakdown, code reviews, and performance feedback for your team. • Contribute hands-on to key development tasks and architecture decisions. • Recruit, mentor, and grow the data science engineering team. Requirements • Proven experience as a Data Scientist. • Proven experience designing and maintaining large-scale data platforms (hundreds of TBs) • 3+ years of proven experience leading and managing a team of data engineers (people management is required) • 4+ years of experience in data science, including a strong Python programming background, advanced SQL skills, and data modeling experience • Expertise with data orchestration tools (Airflow, Prefect, or Dagster) • Cloud platform experience — GCP preferred (AWS/Azure acceptable) • Familiarity with Docker • Strong communication, mentorship, and collaboration skills • BSc/MSc in Mathematics/ physics/ statistics/ Computer Science. • Fluent English (spoken and written) Nice to have: • Experience with Google Cloud Platform tools (BigQuery, Dataflow, Pub/Sub) • Background working with ML pipelines or data science teams • Understanding of data contracts, lineage, and versioning tools • Knowledge of data structures and algorithms • Experience optimizing pipelines and databases for performance and cost • CI/CD pipelines (GitHub/GitLab) • Hands-on experience with distributed data frameworks (Apache Beam, Spark, or similar) • Exposure to airline, pricing, or GDS systems

Itamar At ZOLL, we're passionate about improving patient outcomes and helping save lives. We provide innovative technologies that make a meaningful difference in people's lives. Our medical devices, software and related services are used worldwide to diagnose and treat patients suffering from serious cardiopulmonary and respiratory conditions. ZOLL Itamar is an innovative medical device technology company that focuses on the development and manufacturing of Home Sleep Apnea Tests to aid in the diagnosis of respiratory sleep disorders. Our core product is the WatchPAT®️ family, a revolutionary FDA-cleared portable home sleep apnea test device, that is based on proprietary signal and analysis. 80% of patients who have sleep apnea are undiagnosed. We are committed to reach those undiagnosed patients and provide testing to promote wellness and enhance overall quality of life. WatchPAT®️ is commercially available within major markets including the U.S., Japan, and Europe, and is the leading home sleep apnea test in the US. ZOLL Itamar’s corporate headquarters, research and development and manufacturing are located in Israel with U.S. headquarters based in Atlanta, GA. Job Type Hybrid Job Summary ZOLL Itamar is an innovative medical device technology company that focuses on the development and manufacturing of Home Sleep Apnea Tests to aid in the diagnosis of respiratory sleep disorders. Our core product is the WatchPAT®️ family, a revolutionary FDA-cleared portable home sleep apnea test device, that is based on propriety signal and analysis. 80% of patients who have sleep apnea are undiagnosed. We are committed to reach those undiagnosed patients and provide testing to promote wellness and enhance overall quality of life. WatchPAT®️ is commercially available within major markets including the U.S., Japan, and Europe, and is the leading home sleep apnea test in the US. ZOLL Itamar's corporate headquarters, research and development and manufacturing are located in Israel with U.S. headquarters based in Atlanta, GA. We are looking for a junior algorithm developer to join our team in further development of our products, offering a unique opportunity to combine technology, science, and clinical insight. The job consists of algorithm development – machine learning on unique signals, participating in analyzing and understanding clinical trials, and involvement in feasibility testing of new technologies Essential Functions • The job consists of algorithm developing on our unique signals (signal processing and AI), involvement in feasibility testing of technologies (including setup of new experiments, sensors, and devices) and participating in analyzing and understanding clinical trial. Required/Preferred Education and Experience • Bachelor's Degree BSc (or above) degree in engineering (biomedical, electrical) or science (Physics / Math) from university or the Technion required • Advantage to candidates who • worked with biological signals and in the medical device industry (even as intern or student position). • Have some background in biostatistics • Have hands on experience in experimental setups required Knowledge, Skills and Abilities • Capabilities: Programing skills: Matlab/Python C/C++ (at least basic skills) • Personal capabilities: Eager to learn Capable of working alone and in a multidisciplinary team Interest and ability to learn the physiology and medical aspects – advantage Preferred Languages • English - Advanced Travel Requirements • Centers in Caesarea and Herzliya ZOLL is a fast-growing company that operates in more than 140 countries around the world. Our employees are inspired by a commitment to make a difference in patients' lives, and our culture values innovation, self-motivation and an entrepreneurial spirit. Join us in our efforts to improve outcomes for underserved patients suffering from critical cardiopulmonary conditions and help save more lives.

Speedata is modernizing analytics infrastructure with the first purpose-built ASIC processor, the Analytics Processing Unit (APU), for analytics and AI data workloads. Delivering up to 100x faster Apache Spark performance while cutting infrastructure TCO by 90%, the APU executes analytics operations directly in silicon with seamless integration and no code changes. We are looking for a talented Algorithm Engineer to join our team and help shape the next generation of Speedata's products. In this role, you will develop and optimize algorithms for database operations running on our hardware accelerator, improve performance, and enable new capabilities. You will gain a deep understanding of the entire stack from systems and applications to software and hardware and work across different parts of the codebase. Responsibilities: Researching state-of-the-art algorithms and techniques for data analytics and hardware acceleration Implementing these algorithms in software, then simulating and optimizing their performance Working closely with software and hardware engineers Participating in design reviews and contributing to key design decisions Requirements: BSc or higher in Computer Science, Computer Engineering, Electrical Engineering, or another relevant STEM field 5+ years of software development experience Proven experience in algorithm development Proficiency in Python and C++ Familiarity with computer architecture Excellent communication skills and team player Advantages Experience with database systems and SQL Experience with hardware acceleration systems and ASICs

REAL is building an AI Execution Platform for real estate organizations. Today, the data required to run real estate is scattered across PDFs, spreadsheets, emails, drawings, public records, and disconnected systems, leading to preventable leakage, missed obligations and lost opportunities to improve performance. Used by leading enterprises, REAL converts this fragmented data into connected intelligence and automated action. With advanced AI, universal ingestion, and modular execution agents, REAL increases operational accuracy, uncovers financial discrepancies, and surfaces opportunities to optimize performance and enhance business outcomes. REAL Values Ownership: We take responsibility and move decisively. Clarity: We simplify complexity to deliver meaningful impact. Accuracy: Precision matters, in our product and in how we operate. Velocity: We work with urgency and intent. Partnership: We collaborate closely with our customers and with each other. Role Overview As an AI Algorithm Engineer at REAL, you’ll design and implement advanced algorithmic workflows that power our data digestion pipelines and conversational AI agent experience. You will: • Architect and build workflows that turn raw, unstructured data (e.g., PDF documents and ultra high-resolution architectural drawings) into meaningful, structured context for downstream analysis. • Combine techniques from classical NLP, computer vision, unsupervised learning, and graph theory to build robust end-to-end pipelines - not just standard LLM API calls, but intelligent decomposition, structuring, and context engineering. • Develop AI agent workflows that let customers explore, query, and reason about their data naturally and reliably. • Build strong evaluation infrastructure to benchmark and continuously improve both classical algorithmic components and LLM-based workflows. • Work primarily in Python, and collaborate across systems and services in TypeScript when needed. • Move fast from prototype to production, while maintaining correctness, scalability, and measurable quality. Requirements What You’ll Do Core Responsibilities • Design and implement end-to-end data digestion pipelines for complex unstructured and semi-structured inputs. • Integrate classical algorithms with LLM-centric workflows to produce high-quality contextual inputs for reasoning tasks. • Build systems for segmentation, structure extraction, semantic decomposition, embedding-based representations, and graph construction. • Develop agentic workflows that combine tools, retrieval, and reasoning for interactive customer experiences. • Design evaluation suites, datasets, metrics, and regression tests to measure quality, robustness, and performance over time. • Continuously refine workflows based on customer usage, failure analysis, and measurable improvements. What We're Looking For Required Qualifications • MSc (or equivalent experience) in Computer Science, Mathematics, Electrical Engineering, or a related quantitative field. • 5+ years of experience in data science / algorithm development / applied research engineering roles. • Strong experience building complex algorithmic workflows beyond model calls - including multi-stage pipelines, feature extraction, structure inference, and optimization. • Deep understanding of LLM digestion concepts: RAG, context engineering, chunking strategies, retrieval and ranking, tool usage patterns, and reliability techniques. • Experience designing and maintaining evaluation frameworks for both classical algorithms and LLM workflows (offline + online, regression, benchmarking). • Strong programming skills in Python; familiarity with TypeScript is a plus. • Ability to thrive in a high-ownership startup environment: ambiguity, speed, responsibility, and continuous learning. Nice To Have • Familiarity with vector databases and scalable retrieval architectures. • Familiarity with agent orchestration frameworks (e.g., LangChain) and tool-driven reasoning systems. • Experience deploying AI workflows into production with monitoring, guardrails, and iteration loops. Benefits Why Join REAL • You’ll work on problems that don’t have a pre-scripted solution - it’s a privilege to be among the first to tackle them. • High ownership and direct impact on the core product and architecture. • A fast iteration environment where strong engineers ship meaningful work quickly. • A chance to grow alongside the AI revolution - adapting, learning, and building what’s next.

Description The 4M story is likely one you haven’t heard before: We are on a mission to reveal the world below us—to do for the world below ground what Google Maps did for the world above. By leveraging cutting-edge technology, we are mapping the subsurface infrastructure to make reliable, real-time utility data accessible to the construction industry - completely transforming a traditional industry. We’re a growing startup with 100 employees currently based in Tel Aviv, Israel, and Austin, Texas. The Opportunity  We are looking for a Staff Algorithm Engineer to join our core Algorithm team — a high-autonomy group responsible for the algorithm and ML systems at the heart of 4M's mapping engine. This is a role for engineers who think in systems, bring cutting-edge computer vision and algorithmic thinking to ambitious real-world challenges, and own problems end-to-end with an entrepreneurial drive. In the AI era, being a strong engineer means more than writing great code. It means operating as both an architect and a team lead — designing the solution with clarity, then guiding AI agents to execute it at a level and speed that wasn't possible before. We are building a culture where this is the norm, and we're looking for someone who is excited to work and grow in that direction. You will work across computer vision and algorithm disciplines — researching solutions, designing experiments, and delivering production-grade implementations — while collaborating closely with data engineering and product teams. What You'll Do  • Research and implement novel computer vision and algorithmic solutions for challenging real-world problems — spanning perception, learning, optimization, and graph-based reasoning. • Own algorithm quality end-to-end: design experiments, evaluate results, and drive iterations until production reliability targets are met. • Work across disciplines — sharing models, methods, and insights with algorithm, data engineering, and product teams. • Monitor production model health proactively; identify degradation early and lead remediation efforts. • Integrate AI tools into your workflow and grow into the role of architect and team lead — designing the solution, then directing agents to build it. • Raise the bar on the team's technical culture through code reviews, knowledge-sharing, and rigorous algorithmic thinking. Requirements Required Qualifications  • Relevant B.Sc./M.Sc. with 10+ years of experience as a Computer Vision or Algorithm Engineer, OR relevant Ph.D. with 7+ years of relevant industry experience. • Broad and deep computer vision background, with strong algorithmic foundations — comfortable working across CV and adjacent algorithm domains. • Deep proficiency in deep learning frameworks (PyTorch preferred). • Proficiency in Python — writes clean, production-grade code. • Proven E2E ownership: has taken CV problems from research to production, not just model experimentation. • Strong problem-solving skills — comfortable with ambiguous, non-textbook problems. • Self-motivated and entrepreneurial: identifies gaps, drives solutions, and takes accountability for outcomes. • Mentor and upskill team members, including knowledge sharing and strategic technical development. • Good communication skills — can clearly explain complex algorithmic decisions to both technical and non-technical stakeholders. AI-First Mindset We are building an AI-first engineering culture, and we're looking for engineers who are genuinely excited about working this way. You don't need to arrive with a fully formed AI workflow — but you should have the curiosity and the drive to develop one. In practice, this means: • You're already experimenting with AI tools in your work — code assistants, LLMs, or AI-augmented workflows — and you want to go further. • You're open to learning how to operate as both an architect and a team lead: holding a clear picture of the solution, then directing AI agents to get there. • You see AI not as a threat to engineering craft, but as a multiplier of it. Specific tools and methods can be learned together. What matters is the mindset and the motivation to grow into this way of working. Preferred Qualifications (not required!) • Experience with GIS datasets or geospatial computer vision tasks. • Familiarity with GNN / graph-based algorithms. • Experience with AWS cloud services (SageMaker, S3, EC2). • Background in active learning or AI-assisted annotation pipelines. Why Join 4M If you want to apply cutting-edge computer vision and algorithmic thinking to ambitious, unsolved real-world problems — and see your work directly shape a product that is redefining an industry — this is that role! • Hard, original problems spanning computer vision and algorithm design that push the field forward. No textbook solutions, no incremental improvements on existing products. • CV and algorithms are the core technology driving 4M's mission — your work is the product. • Full end-to-end ownership: from research spike to production, you see the full impact of your work. • You'll grow into operating as both architect and team lead — a scope of influence that compounds over time in ways traditional engineering roles don't offer. • High-autonomy culture that trusts engineers to lead — real responsibility from day one, no micromanagement. • Pre-scale startup (~100 people): your influence on the technical culture, the stack, and the direction is real and lasting.

Description The 4M story is likely one you haven’t heard before: We are on a mission to reveal the world below us—to do for the world below ground what Google Maps did for the world above. By leveraging cutting-edge technology, we are mapping the subsurface infrastructure to make reliable, real-time utility data accessible to the construction industry - completely transforming a traditional industry. We’re a growing startup with 100 employees currently based in Tel Aviv, Israel, and Austin, Texas. The Opportunity We are looking for a Senior Algorithm Engineer to join our core Algorithm team — a high-autonomy group responsible for the algorithm and ML systems at the heart of 4M's mapping engine. This is a role for engineers who think in systems, bring cutting-edge computer vision and algorithmic thinking to ambitious real-world challenges, and own problems end-to-end with an entrepreneurial drive. In the AI era, being a strong engineer means more than writing great code. It means operating as both an architect and a team lead — designing the solution with clarity, then guiding AI agents to execute it at a level and speed that wasn't possible before. We are building a culture where this is the norm, and we're looking for someone who is excited to work and grow in that direction. You will work across computer vision and algorithm disciplines — researching solutions, designing experiments, and delivering production-grade implementations — while collaborating closely with data engineering and product teams. What You'll Do • Research and implement novel computer vision and algorithmic solutions for challenging real-world problems — spanning perception, learning, optimization, and graph-based reasoning. • Own algorithm quality end-to-end: design experiments, evaluate results, and drive iterations until production reliability targets are met. • Work across disciplines — sharing models, methods, and insights with algorithm, data engineering, and product teams. • Monitor production model health proactively; identify degradation early and lead remediation efforts. • Integrate AI tools into your workflow and grow into the role of architect and team lead — designing the solution, then directing agents to build it. • Raise the bar on the team's technical culture through code reviews, knowledge-sharing, and rigorous algorithmic thinking. Requirements Required Qualifications • Relevant B.Sc./M.Sc. with 7+ years of industry experience as a Computer Vision or Algorithm Engineer, OR relevant Ph.D. with 4+ years of relevant industry experience. • Broad and deep computer vision background, with strong algorithmic foundations — comfortable working across CV and adjacent algorithm domains. • Deep proficiency in deep learning frameworks (PyTorch preferred). • Proficiency in Python — writes clean, production-grade code. • Proven E2E ownership: has taken CV problems from research to production, not just model experimentation. • Strong problem-solving skills — comfortable with ambiguous, non-textbook problems. • Self-motivated and entrepreneurial: identifies gaps, drives solutions, and takes accountability for outcomes. • Good communication skills — can clearly explain complex algorithmic decisions to both technical and non-technical stakeholders. AI-First Mindset We are building an AI-first engineering culture, and we're looking for engineers who are genuinely excited about working this way. You don't need to arrive with a fully formed AI workflow — but you should have the curiosity and the drive to develop one. In practice, this means: • You're already experimenting with AI tools in your work — code assistants, LLMs, or AI-augmented workflows — and you want to go further. • You're open to learning how to operate as both an architect and a team lead: holding a clear picture of the solution, then directing AI agents to get there. • You see AI not as a threat to engineering craft, but as a multiplier of it. Specific tools and methods can be learned together. What matters is the mindset and the motivation to grow into this way of working. Preferred Qualifications (not required!) • Experience with GIS datasets or geospatial computer vision tasks. • Familiarity with GNN / graph-based algorithms. • Experience with AWS cloud services (SageMaker, S3, EC2). • Background in active learning or AI-assisted annotation pipelines. Why Join 4M If you want to apply cutting-edge computer vision and algorithmic thinking to ambitious, unsolved real-world problems — and see your work directly shape a product that is redefining an industry — this is that role! • Hard, original problems spanning computer vision and algorithm design that push the field forward. No textbook solutions, no incremental improvements on existing products. • CV and algorithms are the core technology driving 4M's mission — your work is the product. • Full end-to-end ownership: from research spike to production, you see the full impact of your work. • You'll grow into operating as both architect and team lead — a scope of influence that compounds over time in ways traditional engineering roles don't offer. • High-autonomy culture that trusts engineers to lead — real responsibility from day one, no micromanagement. • Pre-scale startup (~100 people): your influence on the technical culture, the stack, and the direction is real and lasting.

Description Exodigo is the leading underground mapping solution for non-intrusive discovery. Our platforms combine multi-sensor fusion, 3D imaging, and AI technologies to create complete, accurate underground maps that enable confident decision-making for customers across the built world. We transform the project lifecycle for our customers, who include key community stakeholders in the utilities, transportation and government sectors. Our customers are the utilities, transportation agencies, and government bodies that build the world's infrastructure — LA Metro, Caltrans, National Grid, Israel Railways, and 100+ teams worldwide. To date we've de-risked $75B in infrastructure investment and mapped 86.1M square feet of ground. We are experiencing sky-rocketing growth and closed a historically large $96M Series B round in July of 2025. Job description Lead the algorithms team within the Geotech group. The team owns the full processing chain, from the raw signal acquired in the field to the output the customer sees: denoising, reconstruction, inversion, detection and characterization of subsurface targets, and quantification of confidence. The data is real field data: noisy, non-ideal, and collected across a diverse sensor suite (GPR, ERT, seismic, EM, magnetometry). This role combines team leadership with hands-on algorithm development, with a strong focus on setting priorities, deciding which directions to pursue or stop, and staying deeply involved in the technical work. This is not management from a distance. Management responsibilities • Translate business needs, customer requirements, and field constraints into a clear algorithmic roadmap with measurable goals and timelines • Set priorities across parallel workstreams, including closing down directions that aren't maturing and freeing the resources tied to them • Protect the team's focus. Shield team members from interruptions and ad-hoc requests that don't serve the roadmap, and manage expectations with the people making those requests • Direct people management: individual goals, ongoing feedback, professional development, hiring and onboarding • Build a measurement culture: define validation methodology, performance metrics, dataset and ground-truth management. Prevent "it looks good" from replacing quantitative proof • Own output quality: code review, engineering standards, reproducibility of results, and documentation good enough to hand work between people • Report status, risks, and decision points to management on an ongoing basis Hands-on engineering • Independently develop and prototype algorithms on the team's hardest problems • Get into the data: analyze failure cases, investigate anomalies, understand what is actually happening in the signal • Work closely with field teams, including going out to the field as needed, to understand noise sources and physical limitations firsthand • Review the team's work at a deep technical level rather than signing off on results Requirements • Proven experience developing algorithms in signal processing, on real physical data (not simulation only) • Strong DSP fundamentals: time- and frequency-domain analysis, filtering, deconvolution, SNR, sampling • Experience with inverse problems and/or reconstruction and imaging (tomography, migration), including handling ill-posed problems and regularization • Full command of Python and the scientific stack (NumPy/SciPy and related), with the ability to write clean, maintainable code rather than one-off scripts • Prior management experience, or at minimum proven technical leadership of several developers and an end-to-end project • Demonstrated ability to make decisions under uncertainty and prioritize between competing directions • Professional-level Hebrew and English Nice to Have • Background in geophysics, or in any field that measures a physical phenomenon through a complex medium (medical imaging, sonar, radar, NDT, seismology, acoustics) • Experience with ML/DL applied to signals and imaging, and the judgment to know when a classical approach is better • Experience taking an algorithm from R&D into production • Familiarity with physical models and forward modeling

Description Exodigo is the leading underground mapping solution for non-intrusive discovery. Our platforms combine multi-sensor fusion, 3D imaging, and AI technologies to create complete, accurate underground maps that enable confident decision-making for customers across the built world. We transform the project lifecycle for our customers, who include key community stakeholders in the utilities, transportation and government sectors. We are experiencing sky-rocketing growth and closed a historically large $96M Series B round in July of 2025. Job description Our Algorithms group is a highly multidisciplinary group at the core of our data processing and detection capabilities, integrating physics, signal processing, computer vision, classical algorithms, and AI models to meet our unique requirements. Our problems are grounded in the physical world: sensor data, engineering drawings, coordinate systems, and the messy reality of infrastructure that was built decades ago and documented inconsistently ever since. Job Description We are looking for an AI Algorithms Engineer to join our Computer Vision team and bring LLMs and agentic AI into problems that are anything but generic. This role is for someone who wants to keep their algorithmic craft and add to it — not trade it in. The interesting work here sits exactly where modern AI meets geometry, vision, and physical measurement, and it needs someone who is genuinely strong on both sides of that line. The work is varied by nature. It can mean finding and making sense of engineering documents that were written by people for people, anchoring what they contain to real-world coordinates, reconciling spatial data from partial and conflicting sources, or building tools and agents inside the professional software our experts work in — platforms such as Civil 3D and ArcGIS. These are separate problems, not stages of one pipeline, and new ones appear regularly. What ties them together is judgment. Some of these problems are a natural fit for LLMs and agents; others are solved far better with geometry, classical computer vision, or a well-chosen heuristic — and many need both. Knowing which is which, and being honest about it, is the single most valuable thing you will bring to this team. Our problems also rarely arrive fully specified. You will often start from a one-line description and an unclear success criterion, in an environment where priorities shift. We are looking for someone who is comfortable in that space — who can decompose an amorphous problem, identify what information is missing, and then go get it: talk to domain experts, dig through data, run a quick experiment, and come back with a sharper definition of the problem than the one they were handed. Key Responsibilities • Own problems end to end — from an ambiguous initial ask, through problem definition and prototyping, to a system that runs reliably in production. • Design and build LLM-powered systems and agentic workflows that automate complex, multi-step tasks involving spatial data, engineering documents, and professional software. • Combine modern AI with classical approaches — including geometry, computer vision, heuristics, and optimization — and make deliberate decisions about which approach best fits each part of the problem. • Work directly with mapping experts, surveyors, and algorithm researchers to understand real-world workflows and turn that understanding into tools people actually use. • Evaluate and integrate new foundation models, frameworks, and techniques, and design evaluation methodologies that determine whether these systems are genuinely reliable on our data. Requirements • 4+ years of hands-on experience building algorithmic, machine learning, or AI systems that were deployed and used in production. • B.Sc. in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a similar field. • A strong algorithmic background is a hard requirement. We are looking for real depth in at least one of the following areas: computer vision, data science, NLP, deep learning, geometry and 3D data, or signal processing. This is the part of the profile we are strict about. • Genuine interest in LLMs and agentic AI, with a practical understanding of how they work and where they fail. You do not need production experience with agents — a side project, prototype, or serious personal exploration is enough, as long as you can walk us through what you built and why. What matters is that you want this to become a real part of your craft. • Comfort working in a dynamic, loosely defined environment. Problems here arrive amorphous and priorities shift. You should be able to take a vague problem, break it into something tractable, identify what information is missing, and go get it — by talking to domain experts, digging through data, or running a quick experiment. • Strong proficiency in Python and solid software engineering practices, including clean, maintainable code and robust systems. Preferred Qualifications • Experience with multimodal and vision-language models, especially for document understanding, drawings, or diagrams. • M.Sc. or Ph.D. in a relevant field. • Experience with geospatial data, GIS, CAD, or coordinate reference systems. • Experience automating or extending professional software through its APIs or plugin ecosystem. • Familiarity with cloud development environments, particularly AWS. A Note on This Role This is deliberately a broad role, and we know that very few people cover all of it. If you have real algorithmic depth and are seriously curious about LLMs and agents — even if your experience with them so far is a side project rather than years of production work — we would like to hear from you. Tell us what you are strong at and what you want to grow into.

Description Exodigo is the leading underground mapping solution for non-intrusive discovery. Our platforms combine multi-sensor fusion, 3D imaging, and AI technologies to create complete, accurate underground maps that enable confident decision-making for customers across the built world. We transform the project lifecycle for our customers, who include key community stakeholders in the utilities, transportation and government sectors. We are experiencing sky-rocketing growth and closed a historically large $96M Series B round in July of 2025. Job description Our Algorithms group is a highly multidisciplinary group at the core of our data processing and detection capabilities, integrating physics, signal processing, computer vision, classical algorithms, and AI models to meet our unique requirements. Our problems are grounded in the physical world: sensor data, engineering drawings, coordinate systems, and the messy reality of infrastructure that was built decades ago and documented inconsistently ever since. We are looking for an Algorithm Developer to join our Algorithms group and work on a new initiative that turns information from beyond our own sensors into geospatial intelligence. This role is for someone with real algorithmic depth who wants to apply it to a problem where the data is messy, the sources are unreliable, and the answer has to be right. The work spans the full path from raw, scattered information to structured intelligence anchored in the real world: finding it, judging what matters, making sense of what it contains, and tying it to coordinates. The sources are inconsistent and the material varies widely in quality and format. Each part is a real algorithmic problem, and none is solved by a single off-the-shelf tool. Knowing which parts suit LLMs and vision-language models, and which are solved far better with geometry, classical computer vision, or a well-chosen heuristic - and being honest about the difference - is the most valuable thing you will bring to this role. Our problems also rarely arrive fully specified. You will often start from a one-line description and an unclear success criterion, in an environment where priorities shift. We are looking for someone who can decompose an amorphous problem, identify what is missing, and go get it - talk to domain experts, dig through data, run a quick experiment - and come back with a sharper definition than the one they were handed. You Will: • Own problems end to end - from an ambiguous initial ask, through problem definition and prototyping, to a system that runs reliably in production. • Build systems that gather information from diverse and inconsistent sources and process it reliably at scale. • Develop methods to judge what is relevant and what is noise, and to measure how much each piece of information can be trusted. • Anchor information extracted from engineering documents and drawings to real-world coordinate systems. • Extract structured data from complex, human-oriented documents, combining classical computer vision, document analysis, and modern LLM-based approaches, with deliberate calls about which fits which part of the problem. • Design evaluation methodologies that measure whether these systems are actually reliable on our data. • Work directly with mapping experts, surveyors, and algorithm researchers to understand real workflows, and turn that understanding into tools people actually use. Requirements • 4+ years of hands-on experience building algorithmic, machine learning, or AI systems that shipped and were used in production. • B.Sc. in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a similar field. • A strong algorithmic background is a hard requirement. We are looking for real depth in at least one of: computer vision, data science, NLP, deep learning, document analysis, or geometry and 3D data. This is the part of the profile we are strict about. • Comfort in a dynamic, loosely defined environment. Problems here arrive amorphous and priorities shift. You should be able to take a vague problem, break it into something tractable, identify what information is missing, and go get it - by talking to domain experts, digging through data, or running a quick experiment. • Strong proficiency in Python, and solid software engineering practices - clean, maintainable code and robust systems, including data pipelines that handle unreliable inputs. • Genuine interest in LLMs and modern AI, and a practical understanding of how they work and where they fail. Production experience is not required - a side project, a prototype, or serious personal exploration is enough, as long as you can walk us through what you built and why. Preferred Qualifications • Experience with problems that combine text and imagery, such as document analysis, drawings, or diagrams, including OCR, layout analysis, and vision-language models. • Experience with geospatial data, GIS, CAD, or coordinate reference systems. • Experience building data collection and processing pipelines over large volumes of unstructured, unreliable data. • M.Sc. or Ph.D. in a relevant field. • Familiarity with cloud environment development (AWS). A note on this role This is deliberately a broad role, and we know that very few people cover all of it. If you have real algorithmic depth and you are seriously curious about applying it to documents, geometry, and the messy reality of infrastructure - even if you have not worked on all of it before - we would like to hear from you. Tell us what you are strong at and what you want to grow into.

Description Exodigo is the leading underground mapping solution for non-intrusive discovery. Our platforms combine multi-sensor fusion, 3D imaging, and AI technologies to create complete, accurate underground maps that enable confident decision-making for customers across the built world. We transform the project lifecycle for our customers, who include key community stakeholders in the utilities, transportation and government sectors. Our customers are the utilities, transportation agencies, and government bodies that build the world's infrastructure — LA Metro, Caltrans, National Grid, Israel Railways, and 100+ teams worldwide. To date we've de-risked $75B in infrastructure investment and mapped 86.1M square feet of ground. We are experiencing sky-rocketing growth and closed a historically large $96M Series B round in July of 2025. Job description Our Algorithms Team is a highly multidisciplinary group spanning physics, signal processing, computer vision, classical machine learning, and modern AI models, built around problems that don't have off-the-shelf solutions. As an Algorithm Engineer on Exodigo's Algorithms Team, you'll build the algorithms that turn raw subsurface signals into an accurate map — automating and outperforming work that today only geophysicists and civil engineering experts can do. You'll work across the full span of our data: multi-sensor field acquisitions, and the existing record of what's already known underground. The hard part is the fusion — reconciling physics-driven detections with incomplete and contradictory records into a single coherent picture of the subsurface. You'll work directly with our mapping and engineering experts to validate what you build, and with our software team to get it into the production pipeline. Responsibilities • Translate real-world physical and engineering problems into mathematical models and algorithmic solutions. • Design algorithms that fuse heterogeneous sources — sensor modalities with different physics and resolution, alongside vector, raster, tabular, and unstructured data. • Extract structure from noisy signal: detection, segmentation, and interpretation where ground truth is scarce and the physics is only partly cooperative. • Build evaluation methodology alongside the algorithms, so downstream engineers know what to trust and how much. • Partner with the maps analysis team to test, benchmark, and iterate on performance. Requirements • B.Sc. in technical field such as Electrical Engineering, Computer Engineering, Computer Science or similar. • 5+ years of relevant industry experience. • Solid grounding in machine learning, with judgment about when a classical method beats a deep model. • Expertise in graph theory, computational geometry, statistics, optimization, and data analysis. • Strong Python programming skills (Pandas, NumPy, SciPy, PyTorch, etc.). • Versatility in selecting and combining tools to fit the problem at hand. Nice to Have • M.Sc. in relevant field. • Experience in Geo Information Systems (GIS). • Experience working with BIM data and 3D modelling. • Experience applying LLMs to information extraction from unstructured or scanned documents. • Experience in cloud environment development (AWS).

You'll join Mobileye's REM (Road Experience Management) department. REM is an end-to-end mapping and localization engine that supports full autonomy capabilities and services. Building validation processes and methods for a technology of this scale is challenging, meaningful and rewarding work. The system is complex and based on machine learning and image processing, so analysis and validation take deep thinking and strong technical and analytical skills. You'll develop validation infrastructure, tools and methods using cutting-edge technology and cloud-based applications. We use AI wherever it helps: to automate routine work, improve code quality and make our development process more efficient. What your job will look like: • Plan and build advanced, end-to-end validation processes for REM mapping and localization. • Build validation tools that use geometric calculations, logic and heuristics. • Add new features to the validation pipeline and make it more sensitive, faster and better. • Use AI tools to improve the development process, for example automated code review, unit-test generation and automating repetitive tasks. • Work with algorithms and tools from other R&D groups and build them into the validation infrastructure. • Analyze large-scale data on the cloud and turn the results into clear conclusions. All you need is: • B.Sc. in Computer Science, Software Engineering or a related field. • 3+ years of hands-on software development, with Python in production (Pandas, NumPy, SciPy, etc.). • Good coding practice: Git, testing, CI/CD. • Daily, hands-on use of AI coding assistants and agents (e.g., GitHub Copilot, Claude Code, Cursor). • A critical eye for AI output: reviewing, testing and checking AI-generated code and results. • Strong analytical skills, with broad vision and technical depth. • Good communication and teamwork across groups. • Fluent English. Nice to have: • Experience automating development and data workflows with LLM-based tools and agents. • Knowledge of descriptive statistics, probability and statistical inference. • Geometry or geospatial work (Shapely, GeoPandas, coordinate systems). • Cloud and distributed processing (AWS S3/Athena, SQL, Spark/PySpark). • Computer vision, ML or mapping/localization. Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

Our vision Localization group is responsible for accurately localizing the vehicle on a high-definition 3D map with centimeter-level precision using surround camera systems to enable autonomous driving. Our work combines advanced geometric reasoning, scene understanding, and large-scale mapping to solve one of the core challenges of autonomous vehicles in complex real-world environments. The role involves developing algorithmic and deep learning solutions that integrate mathematical optimization, computer vision, and 3D geometry. We work with modern neural network architectures including Transformers, GNNs, and CNNs to solve problems involving scene understanding, object association, and precise spatial reasoning in dynamic environments. The HD map contains rich geometric and semantic information that is critical for safe driving and cannot always be inferred reliably from images alone under all visibility conditions or viewpoints. In addition to achieving highly accurate localization, the team is also responsible for estimating map relevance and consistency with the current world state to ensure safe and reliable autonomous driving. What will your job look like: • Develop state-of-the-art localization algorithms for autonomous driving using multi-camera surround vision systems. • Design and implement deep learning models based on Transformers, Graph Neural Networks, and Convolutional Neural Networks. • Solve challenging problems involving 3D geometry, scene understanding, object matching, and spatial reasoning. • Combine learning-based methods with classical optimization and geometric algorithms. • Own the entire lifecycle from prototyping to deployment. • Analyze real-world driving data and improve system robustness under diverse environmental and visibility conditions. • Drive innovative solutions for high-precision localization at production scale. All you need is: • 2+ years of practical experience developing computer vision or machine learning solutions using Python and frameworks such as PyTorch or TensorFlow – must. • B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or a related field, with strong academic performance. • Solid foundation in algorithms, data structures, and computer vision/deep learning fundamentals. • Strong analytical skills, a sense of ownership, and the ability to work collaboratively. Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

Our vision Localization group is responsible for accurately localizing the vehicle on a high-definition 3D map with centimeter-level precision using surround camera systems to enable autonomous driving. Our work combines advanced geometric reasoning, scene understanding, and large-scale mapping to solve one of the core challenges of autonomous vehicles in complex real-world environments. The role involves developing algorithmic and deep learning solutions that integrate mathematical optimization, computer vision, and 3D geometry. We work with modern neural network architectures including Transformers, GNNs, and CNNs to solve problems involving scene understanding, object association, and precise spatial reasoning in dynamic environments. The HD map contains rich geometric and semantic information that is critical for safe driving and cannot always be inferred reliably from images alone under all visibility conditions or viewpoints. In addition to achieving highly accurate localization, the team is also responsible for estimating map relevance and consistency with the current world state to ensure safe and reliable autonomous driving. What will your job look like: • Develop state-of-the-art localization algorithms for autonomous driving using multi-camera surround vision systems. • Design and implement deep learning models based on Transformers, Graph Neural Networks, and Convolutional Neural Networks. • Solve challenging problems involving 3D geometry, scene understanding, object matching, and spatial reasoning. • Combine learning-based methods with classical optimization and geometric algorithms. • Own the entire lifecycle from prototyping to deployment. • Analyze real-world driving data and improve system robustness under diverse environmental and visibility conditions. • Drive innovative solutions for high-precision localization at production scale. All you need is: • 5+ years of practical experience developing computer vision or machine learning solutions using Python and frameworks such as PyTorch or TensorFlow – must. • B.Sc. or M.Sc. in Computer Science, Electrical Engineering, or a related field, with strong academic performance. • Solid foundation in algorithms, data structures, and computer vision/deep learning fundamentals. • Strong analytical skills, a sense of ownership, and the ability to work collaboratively. Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

We are looking for a Senior ML Algorithm Engineer to lead the development and optimization of machine learning models for challenging real-world problems. In this role, you will work hands-on across the full model-development lifecycle: understanding the task, designing and adapting algorithms, building effective training strategies, analyzing data and failure modes, and improving model quality and efficiency through rigorous experimentation. This is an algorithm-focused role for someone who enjoys getting deeply involved in the details of model training and optimization. You will not simply operate an existing training infrastructure—you will investigate open-ended problems and develop practical solutions involving model architecture, data and sample selection, training objectives, optimization methods, and evaluation What will your job look like: • Work on the semantics of road objects, using harvested tabular data as the primary input to our algorithms — turning large-scale, real-world observations into models that capture object meaning, attributes, and behavior on the road network. • Design, implement, and optimize machine learning and deep learning algorithms for these semantic tasks, from architecture and training objectives through evaluation and efficiency. • Develop and improve end-to-end model training pipelines, from data preparation and sampling of harvested tabular datasets through training and evaluation. • Investigate model behavior, identify failure modes, and drive targeted algorithmic improvements. • Develop effective strategies for data selection, dataset composition, sampling, augmentation, loss design, and training schedules. • Lead the investigation of complex algorithmic challenges, uncover patterns in data and model behavior, and translate insights into measurable improvements. All you need is: • 5+ years of experience in algorithm engineering using machine learning, deep learning, or neural networks. • Strong hands-on experience designing, training, evaluating, and optimizing. • Strong programming skills in Python. • Hands on experience with Spark, Pandas, Pytorch and AWS. • Experience with Polars and DuckDB- an advantage • Experience with some of the following: sampling strategies, data augmentation, hyperparameter optimization • Strong understanding of distributed systems, scalability, and performance optimization. • Ability to independently investigate complex problems, identify patterns in data and model behavior, run experiments, and translate findings into measurable algorithmic improvements. • Strong analytical and problem-solving skills, with a practical, hands-on, and ownership-driven mindset. Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!