Top Machine Learning Jobs in Israel

Lead the Payment Fraud product roadmap to maximize approvals and minimize fraud by partnering with engineering, data science, analysts, and sales. Drive new market entry through vertical research, merchant engagement, pilot programs, and performance tracking (approval rates, fraud rates, chargeback impact).

Design and build AI-driven developer workflows and agents within Datadog, from prototyping to production. Implement prompt engineering, evals, and integrations with developer tools and extensions. Collaborate with product teams to productionize LLM-based features (e.g., debugging agents), iterate with users, and follow LLM/agent research to improve developer productivity.

The AI Engineer is responsible for designing, implementing, and deploying AI systems and applications, focusing on machine learning models and large language models (LLMs).

Lead the AI-first product strategy for monday service, owning discovery, roadmap, and execution. Collaborate with engineering, design, data science, and GTM teams to build AI/ML/LLM-powered service workflows, validate ideas via experiments and research, and represent Service AI internally and externally.

Lead product strategy and execution for human-agent collaboration surfaces (boards, dashboards, composable UI). Define agentic workflows, delegation, review, and contextual UX; partner with design, engineering, and cross-platform PMs; engage customers; iterate quickly in ambiguous, fast-moving AI product space to scale agentic experiences for millions of users.

The role involves advancing LTX-Video models, designing machine learning models, conducting experiments in generative media, and collaborating across teams to implement impactful features.

Lead vision and roadmap for an AI-powered no-code app builder. Drive ideation, prototyping, and validation of generative AI features. Lead cross-functional teams to deliver and scale product impact, define success metrics, and partner with GTM and customer success to drive adoption and integrations across the monday platform.

Lead production ML efforts for marketing and growth: build and maintain models (ARR prediction, lead scoring), own experimentation infrastructure, mentor analysts, deploy LLM/agentic solutions, and drive end-to-end impact from ideation through production and adoption.

Lead the Policy Protect product to detect and prevent ecommerce policy abuse. Collaborate with data science and engineering to build and maintain ML models, ensure analysis scalability and reliability, define KPIs, prioritize the product backlog, and drive sales opportunities by engaging merchants and partners.

As a Data Science Team Lead, you will manage a team of Data Scientists, collaborate with cross-functional teams, develop machine learning models, and oversee their integration into production systems.

Design, prototype and implement digital image and video processing algorithms for electro-optics systems. Write high-quality C++/Python code, integrate new techniques into existing systems, collaborate with software and hardware teams for on-chip implementation, and present results. MATLAB/Simulink and ML experience are advantages.

Lead technical projects in the System Product Engineering group by managing project lifecycles, collaborating with multiple teams, and improving product quality through advanced testing and analysis.

Lead research initiatives to enhance AI products, drive innovation, and collaborate across teams to meet customer needs in AI solutions.

Lead the transition to a self-hosted LLM ecosystem, optimizing model inference, developing agentic workflows, and executing fine-tuning strategies for chatbot enhancement.

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.

Develop and optimize signal-processing and embedded ML algorithms for animal monitoring systems across edge and cloud platforms. Analyze datasets, train and tune models for constrained devices, collaborate with hardware/firmware/software teams for production integration, establish validation best practices, write production-quality code, and document results.

Lead foundry-facing engineering to drive yield and performance across advanced nodes. Analyze large IC parametric datasets, develop data pipelines, build automated monitoring/alerting, and coordinate cross-functional teams and foundry partners to identify and contain process excursions.

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

The role involves architecting AI verification methodologies, developing AI tools for formal verification, and collaborating with CAD teams to enhance automation workflows.

Develop AI and LLM-based solutions to enhance design and verification processes, collaborating with cross-functional teams for efficiency.

As a Senior LLM Agents Architect, you will research and prototype AI solutions, deploy ML models, contribute to architecture design, and collaborate with teams to deliver AI-powered solutions.

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.

Define and design SoC/IP architecture, collaborate with cross-functional teams, lead technical discussions, drive architectural decisions, and manage functional safety compliance.

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.

The Research Scientist will evaluate and develop AI models for new sensing modalities, prototype hardware, and benchmark new technologies against current inspection methods.