Algorithm Engineer jobs in Tel Aviv-Yafo

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 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

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 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 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.

Realize your potential by joining the leading performance-driven advertising company! As a Senior ML Engineer on the Matchmaking and Marketplace R&D unit in our Tel Aviv office, you’ll play a vital role in building machine learning models that power Taboola’s real-time auctioneer and optimize billions of daily auctions. You’ll design and evolve large-scale ML solutions that drive advertiser bids and expected outcomes for advertisers, publishers and Taboola itself. Working at the intersection of machine learning, data, and engineering, you’ll take models from research and experimentation through production, creating solutions that directly impact advertiser performance, publisher revenue, and marketplace efficiency. To thrive in this role, you'll need: • 4+ years of experience building machine learning and deep learning solutions end-to-end, from research and experimentation through production. • MSc or PhD in Computer Science, Mathematics, Engineering, Statistics, or a related field, with strong foundations in machine learning, optimization, and statistical modeling. • Strong software engineering skills in Python or Java, with experience developing production ML systems. • Proven ability to take machine learning models from prototype to scalable, high-performance production environments. • Experience using AI coding tools (such as Claude Code or Cursor) to accelerate development, experimentation, and code quality. Bonus points if you have: • Experience in the recommendation system domain How you'll make an impact: • Design, train, and deploy machine learning models for CTR/CVR/value prediction • Own the full machine learning lifecycle, from research and prototyping through production deployment, A/B testing, monitoring, and optimization. • Build and evolve large-scale ML models serving low-latency, high-throughput production traffic. • Analyze auction and marketplace data to identify modeling opportunities and translate insights into measurable business impact. • Partner with Product, Engineering, and Business teams to translate marketplace goals into scalable machine learning solutions. • Mentor junior engineers and contribute to technical design reviews, code reviews, and deep technical investigations. Why Taboola? If you ask Taboolars what they love about working here, they’ll tell you that they’ve been empowered to realize their full potential while growing and learning from and with smart and talented people. They’ll also share more about: • Adam Singolda, Taboola Founder and CEO: “You can copy anything from another business but you can’t copy a company’s culture.” • Well-being: Competitive benefits and well-being programs tailored to the region, including comprehensive health benefits, a fully stocked kitchen, and location-specific perks. • Flexibility: We offer a hybrid work schedule with 3 days in-office, with an option to come in more often if desired. • Work with some of the biggest names: Our publisher partners include Yahoo, Conde Nast, Fox Sports, NBCU, ESPN, CBS, and E! Online. Our advertiser clients include Wells Fargo, Honda, Pinterest, and Expedia. Ready to realize your potential? Taboola is an equal opportunity employer and we value diversity in all forms. We are committed to creating an inclusive environment for all employees and believe such an environment is critical for success. Employment is decided on the basis of qualifications, merit, and business need. Learn more about #TaboolaLife on LinkedIn, Facebook, Instagram, X, YouTube, & the Taboola Life Blog. About Taboola Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social and delivers measurable outcomes at scale. Taboola works with thousands of businesses who advertise directly on Realize, Taboola’s powerful ad platform, reaching approximately 600M daily active users across some of the best publishers in the world. Publishers like NBC News, Yahoo, and OEMs such as Samsung, Xiaomi and others use Taboola’s technology to grow audience and revenue, enabling Realize to offer unique data, specialized algorithms, and unmatched scale. #LI-DN1 #LI-Hybrid