Top Machine Learning Jobs in Israel

Design, build, and deploy scalable Go-based backend microservices for a cloud-native SaaS identity analytics product. Contribute to architecture, CI/CD pipelines, tests (unit and end-to-end), code reviews, and DevOps workflows; integrate AI-assisted tooling; mentor junior engineers and collaborate with product management to improve performance and scalability.

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.

Lead development of an AI-powered travel mobile app: design conversational UX, architect and implement Swift-based features (SwiftUI, Combine), collaborate with AI engineers, and build context-aware, personalized mobile experiences.

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.

CrowdStrike seeks a Senior Intelligence Analyst to provide threat intelligence and digital risk monitoring, collaborating with teams to deliver customer-focused solutions and presentations, while maintaining customer relationships.

Lead and grow a distributed engineering organization building customer-facing security capabilities: proprietary scanners, AI/ML detection engines, agentic remediation, vulnerability management, and security foundations. Set vision and roadmap, drive architecture and delivery, partner with product management, establish engineering standards, and represent the group in cross-functional and customer forums.

Design, train, and deploy large-scale machine learning models for bid optimization, price and win-rate prediction, CTR/CVR estimation, and auction optimization. Own the full ML lifecycle—research, experimentation, production deployment, A/B testing, monitoring, and optimization—while partnering with Product, Engineering, and Business teams and mentoring junior scientists.

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).

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

Design and implement end-to-end validation infrastructure, tools, and methods for REM mapping and localization. Develop automated validation processes, integrate algorithms and features, improve sensitivity and efficiency, and manage daily priorities while collaborating across 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.

Own end-to-end delivery for a portfolio of cross-functional initiatives across AI, Platform, Data and Product. Lead quarterly planning, milestone and risk tracking, budget management, dependency resolution, and reporting. Partner with engineering managers, architects, and stakeholders, maintain Jira and sprint hygiene, build visibility tooling, and translate status and risks into clear updates for leadership.

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.

Contribute to design, develop, test, and maintain AI-powered features and services. Implement production-quality code, build agents, prompt and retrieval workflows, run evaluations and monitoring, debug issues, and apply CI/CD, security, and responsible AI practices while collaborating with mentors and cross-functional team members.

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.

Design, develop, and deploy machine learning models for risk, fraud, and operations. Operate training/deployment infrastructure, analyze multiple data sources, conduct model impact research, and integrate models into production backend systems to improve portfolio performance.

Lead and mentor a data science team, define data strategy, manage end-to-end ML projects, analyze large datasets, build algorithmic solutions, and communicate insights to senior leaders to support revenue-driving decisions.

Design, build, and maintain scalable ETL/ELT pipelines and data solutions. Integrate and model data across sources, ensure data quality and governance, develop complex SQL and DBT transformations, and operationalize AI/ML and generative AI workflows from prototype to production while supporting global stakeholders.

As a Senior Data Scientist, you will architect and implement machine learning models, influence strategy, mentor others, and tackle complex challenges in a high-stakes environment.

The NLP Data Science Researcher will develop advanced NLP, LLM, and Agentic AI systems while collaborating on analytics initiatives and transitioning prototypes to production, focusing on customer engagement solutions.

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.