Top Machine Learning Jobs in Israel

Lead car insurance pricing strategy by identifying opportunities, building and improving pricing and risk models using actuarial methods, ML and AI tools, partnering with Data Science, Product, Engineering and Finance, defining metrics (loss ratio, rate adequacy, conversion, retention), and translating complex pricing problems into scalable product and platform requirements.

Research and build end-to-end multi-camera 3D perception models combining geometry and semantics for autonomous vehicles. Work on 3D semantic occupancy, reconstruction, detection, multi-view fusion, and production deployment on vehicles.

Lead product vision, strategy, and roadmap for the Velocity TDIR platform. Drive evolution to an AI-powered MDR/Security Operations platform, partner with security and engineering teams, engage customers, prioritize product investments, and measure adoption, analyst efficiency, and market differentiation.

Lead technical presales activities and act as the primary advisor for customers, providing solutions and demonstrations while driving RFI and RFP responses.

Design, build, and deploy production ML systems for a mobile-gaming loyalty platform using high-volume behavioral data. Create real-time models for marketplace matching, dynamic pricing, personalized recommendations, fraud detection, and game-economy simulation, owning end-to-end delivery and iteration.

The Senior Program Manager will lead multiple squads, manage project workflows, collaborate on cybersecurity solutions, and drive innovation and team performance.

Design, implement, and maintain real-time blockchain detection systems. Analyze large datasets, develop and test heuristics and scoring logic, investigate incidents, and partner with researchers to operationalize and tune production detection modules.

The HR Director will lead HR initiatives in Israel, ensure compliance with local laws, support hiring and performance management, and act as a trusted advisor to leaders while fostering a positive employee experience.

As a Full Stack Developer, you will develop and manage web applications, collaborate with Data Scientists, optimize databases, and lead technology initiatives in healthcare.

Lead product definition for ATE and System Test solutions, oversee product vision, roadmap, and coordinate with cross-functional teams to enhance semiconductor testing quality and scalability.

Lead post-silicon and system-level data analysis to diagnose silicon and system issues, integrate proteanTecs analytics into customer environments, support customers, and collaborate with R&D and data science to validate and improve analytics solutions.

Drive territory development and close new business with Digital Native and enterprise accounts. Build relationships from engineers to executives, evangelize Aerospike solutions, manage pipeline and forecasts in Salesforce, deliver technical presentations, and support regional events to exceed quota.

Develop algorithmic solutions in e-beam inspection, focusing on computer vision and machine learning. Involves end-to-end delivery to customers.

Design, develop, and debug backend software for distributed metrology systems; define specifications; collaborate with internal and external stakeholders; perform testing and troubleshooting; produce documentation and reports; influence architecture and deliver complex features within Agile R&D teams.

Lead a multidisciplinary team to define and deliver physical, mathematical, and AI-enabled modeling solutions for advanced semiconductor metrology. Own roadmap, bridge research to product, build partnerships, scout emerging trends, and grow technical capabilities to achieve sub-nanometer accuracy.

As an Applied AI Engineer, you will develop machine learning models, integrate AI tools into workflows, and analyze security risks utilizing AI.

Design and implement fault-tolerant, scalable backend cloud services including managed databases, managed Kubernetes, billing, monitoring, and ML services. Debug complex issues, write reliable production code, and collaborate across distributed engineering teams.

Customer-facing application engineer who deploys and optimizes Cadence verification tools (simulation, low-power, UVM/SystemVerilog, AI-driven workflows). Duties include debugging complex designs, enabling customer adoption, delivering trainings/POCs, and collaborating with R&D to influence product improvements.

Research and develop algorithms for autonomous driving planning and decision-making. Model real-world driving scenarios as optimization, learning, or algorithmic problems. Apply classical algorithms, ML and deep learning, analyze large-scale driving data, and implement production-quality C++/Python code while building on state-of-the-art literature.

The AI Researcher will research advanced AI model capabilities, develop assessment methodologies, create mitigation solutions, and support product development.

As a Research Engineer, you'll develop systems to evaluate and secure frontier AI models, create testing frameworks, and contribute to team projects and research publications.

Lead product development for AI-driven retail solutions from research to delivery, collaborate with R&D, Business, Marketing and Operations, build roadmaps with strategic clients, and manage enterprise customer relationships for computer-vision and ML products.

Build and own end-to-end features for an AI-powered email security platform, implementing frontend UIs (React/TypeScript) and backend services (Python), writing tests (Playwright/E2E), designing scalable APIs, collaborating on architecture and product decisions, and improving the engineering lifecycle and tooling.

Build and maintain benchmarking and evaluation infrastructure for foundation and multimodal models. Design abstractions/APIs, implement metrics, integrate models and baselines, support model development, debug evaluations, and ensure reproducible, versioned workflows.

Lead backend development for Sunbit's Risk Team building low-latency, high-throughput microservices that operationalize predictive ML models. Design, scale, and maintain resilient distributed systems, collaborate with ML engineers and product teams, drive technical excellence, and mentor junior engineers.