Top Machine Learning Jobs in Israel

Lead system-level hardware testability architecture for NVIDIA networking products across the product lifecycle. Define hardware, software, firmware, fixtures, and cabling test solutions; maximize test coverage; create specifications and production test flows; present testing architectures; support production ramp-up and engineering changes; assess DFT risks; and coordinate cross-functional teams, contract manufacturers, and suppliers.

Own production optimization of LLM and VLM inference systems, improving latency, throughput, memory efficiency, GPU utilization, quality, reliability, and cost. Deploy and benchmark inference engines, build compression and quantization workflows, implement acceleration techniques, diagnose serving bottlenecks, and collaborate with kernel, platform, research, product, and customer teams.

Design, build, and improve machine learning software products using large-scale textual data, NLP, deep learning, LLMs, and generative AI. Develop models, analyze data, create production-ready prototypes, integrate services, and monitor quality and performance through evaluation and metrics. Collaborate with product, engineering, and research teams to deliver data-driven talent solutions.

Owns cross-functional delivery of Sunbit’s credit risk decisioning platform across Card, BNPL, and emerging products. Responsibilities include coordinating ML, engineering, business, compliance, legal, and operations stakeholders; managing requirements, roadmaps, backlogs, dependencies, launches, experimentation, and performance monitoring; and improving underwriting automation, approval decisions, pricing, loss management, regulatory integrity, and customer outcomes.

Own Sedric’s AI reference architecture across services, agents, retrieval systems, evaluation pipelines, and infrastructure. Define reusable patterns and standards, lead architecture reviews, evaluate vendors and foundation models, and shape the technology roadmap. Build production agentic systems, governance frameworks, and evaluation harnesses while partnering with Product, Engineering, customers, and executives. The role combines hands-on delivery with organization-wide technical leadership, including shipping LLM improvements and optimizing latency and reliability.

Design, build, and maintain full‑stack web applications and interactive data visualizations; create prototypes and MVPs; implement backend services and APIs; work with cloud infrastructure and deployment pipelines (AWS); participate in architecture and code reviews; write clean, tested code and collaborate with product, design, and engineering teams.

Arago is seeking ongoing applications for a dynamic range of roles related to AI and hardware, encouraging candidates to submit their details for consideration.

The role involves designing advanced AI models for cybersecurity solutions, leading research initiatives, and mentoring data scientists, focusing on LLMs and scalable systems.

Senior backend engineer to lead design and implement high-scale XDR detection systems. Build and maintain Big Data/ETL pipelines, optimize databases, collaborate with Product/Frontend/ML/DevOps, and deploy production-ready, low-latency detection services.

Build and scale production machine learning infrastructure, including training and inference pipelines, model deployment, feature generation, registries, monitoring, governance, and CI/CD. Improve reliability, reproducibility, observability, performance, and cost efficiency across ML systems. Collaborate with data scientists, analysts, and engineers to productionize models, establish technical standards, and guide the platform roadmap.

As a CBRN expert at Alice.io, you will evaluate and create prompts for Generative AI systems, ensuring their safety and accuracy in CBRN contexts. You'll provide expert feedback and stay updated with relevant research and regulations.

Research, design, and implement advanced algorithms for 3D semiconductor metrology. Apply computer vision, machine learning, signal processing, and probabilistic modeling to analyze complex datasets, estimate error bounds, and validate solutions in collaboration with physicists, system engineers, and software developers.

Own a product area end-to-end: set strategy, define roadmap, write requirements and user stories, lead discovery with customers, prioritize backlog, collaborate with UX, R&D, sales and leadership, and drive execution for utility-focused SaaS products.

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.

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.

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.

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.

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.