Algorithm Engineer jobs in Israel

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 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. 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).

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. 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.