Top Machine Learning Jobs in Israel

Lead technical product strategy and roadmap for AI-driven, hardware-accelerated video analytics products. Define specifications, prioritize features, set performance and cost benchmarks, collaborate with engineering, gather customer feedback worldwide, and translate technical and market inputs into product requirements and designs.

Conducts research on generative world models and diffusion-based systems for autonomous driving. Designs, trains, and evaluates large-scale multimodal models using distributed multi-GPU infrastructure, fleet-scale datasets, and rigorous scenario-based evaluation. Develops controllable, temporally consistent driving simulations and collaborates with perception, policy, data, simulation, and validation teams to improve autonomy KPIs. Publishes research and advances generative AI technologies for L3 autonomous driving.

Develop and deploy production-grade machine learning models for fraud, risk, and ecommerce challenges. Responsibilities include problem framing, model design and evaluation, feature engineering, large-scale data analysis, production deployment, and exploring modern ML and generative AI techniques. The role collaborates with data engineers, developers, and product managers to translate quantitative insights into business impact.

Own the payments product roadmap focused on improving payment conversion, approval rates, and fraud reduction. Optimize authentication, authorization, checkout flows, and alternative payment methods across global markets. Partner with merchants, Sales, Account Management, Engineering, Data Science, Analytics, and GTM to launch capabilities, support expansion, analyze product metrics, develop market benchmarks, and track competitors and regulatory trends.

Build and own end-to-end machine learning and generative AI solutions for cybersecurity vulnerability management, detection, prioritization, and remediation. Design production-ready models and pipelines in Python using AWS and Spark, integrate LLM workflows, and deploy scalable systems. Collaborate with researchers, data engineers, and product leaders to translate cybersecurity challenges into impactful AI capabilities.

The Sales Engineer will support enterprise sales across EMEA by leading technical discovery, solution design, product demonstrations, proofs of concept, RFP responses, and technical presentations. The role advises prospects on fraud prevention, chargeback mitigation, payment optimization, and risk management. It partners with Sales, Product, Engineering, Implementation, and Customer Success teams, translates customer requirements into technical specifications, and supports handoffs. Strong expertise in ecommerce, payments, fraud prevention, APIs, and enterprise stakeholder communication is required.

Lead product strategy for a performance advertising platform, optimizing bidding logic, serving algorithms, prediction systems, and marketplace dynamics. Partner with Data Science, R&D, analytics, and business teams to translate complex algorithms into scalable capabilities, improve advertiser ROI and conversion rates, and balance advertiser demand with publisher supply. Design and interpret large-scale A/B tests, identify optimization opportunities, and guide cross-functional product launches.

Own the vision, strategy, roadmap, and execution for monday CRM Sales. Lead development of AI-powered agentic experiences that automate sales workflows, surface insights, and improve deal execution. Collaborate with engineering, design, AI/ML, data, analytics, sales, customer success, and GTM teams. Use customer feedback and quantitative metrics to prioritize products across desktop and mobile.

Research and develop production machine learning systems for audio and video transcription, analysis, understanding, and editing. Explore NLP, deep learning, and related methodologies; train and evaluate models using distributed GPU resources; improve AI system performance, efficiency, and scalability; and collaborate with product and engineering teams to deliver innovative features.

Develop and maintain complex full-stack software applications with a strong Python backend focus. Design algorithms, build new features, test and debug systems, and collaborate with cross-functional teams. The role involves cloud platforms, machine learning, client-server architecture, AI coding assistants, and potentially Airflow, data warehouses, databases, SQL, and multithreaded environments.

Design, build, deploy, and operate the core engine for Pentera’s AI Autonomous Attacker. Develop production agentic workflows combining deterministic logic, LLMs, and ML models to discover vulnerabilities and conduct authorized security testing. Collaborate with security researchers, data scientists, and DevOps engineers, while creating evaluations and benchmarks to improve system effectiveness, reliability, precision, and performance.

Develops deep learning algorithms and computer vision solutions for 2D and 3D sensing in autonomous vehicles. Responsibilities include designing neural networks, owning end-to-end deep learning projects, defining requirements, researching advanced architectures, and collaborating cross-functionally. The role covers data preparation, model training, validation, deployment, and improving existing algorithms using frameworks such as PyTorch and Python.

Develop machine learning algorithms and data-driven models for geophysical and subsurface engineering applications. Research emerging ML technologies, optimize large-scale workloads for high-performance computing, and collaborate with data scientists, engineers, product teams, and customers. The role involves handling large datasets, developing neural-network solutions, integrating innovative technologies into software applications, and supporting continuous innovation in the geophysical domain.

Provides technical presales solutions for data, analytics, AI, and machine learning opportunities across EMEA. Advises customers on data strategies, conducts workshops and feasibility assessments, develops action plans, creates AI demos and proofs of concept, and collaborates with sales, delivery teams, vendors, and partners. Presents use cases and strategic recommendations to technical and business stakeholders.

Explore frontier AI techniques for security applications, including reasoning models, autonomous agents, reinforcement learning, fine-tuning, and retrieval-augmented generation. Design experiments, develop novel model-adaptation methods, build evaluation frameworks, validate AI solutions, and collaborate with engineering and product teams to transition successful research into products.

Lead and support AI transformation and digital strategy projects for global organizations. Analyze business challenges, identify AI and data opportunities, develop roadmaps and business cases, assess AI maturity and technologies, translate business needs into technical requirements, facilitate workshops, and collaborate with stakeholders to drive AI adoption and data-driven decision-making.

Leads large-scale, multidisciplinary AI processor R&D programs from architecture through production and customer delivery. Coordinates hardware, algorithms, firmware, embedded software, toolchains, verification, and systems teams of 30+ engineers across global sites. Owns planning, schedules, risks, quality, KPIs, change control, PMO processes, customer communication, and executive reporting for NPU and edge AI products.

Lead technical sales engagements for Snowflake’s data cloud platform in Israel. Partner with account teams, channel partners, and customers to understand requirements, demonstrate solutions, conduct proofs of concept, develop technical champions, and guide architecture and implementation decisions. Present to executives and technical audiences, stay current on data and AI technologies, collaborate with Product, Engineering, Marketing, and partners, and support account and territory strategies.

Drive yield and performance improvements for advanced-node ICs through semiconductor process analysis, data pipelines, and automated monitoring. Serve as the technical interface with foundry partners, investigate process excursions, identify yield limiters, and lead issues to containment. Collaborate with cross-functional engineering, test, reliability, and operations teams while applying Python-based automation, visualization, and AI/ML techniques to optimize manufacturing performance.

Develop and maintain AI, computer vision, image processing, and deep learning algorithms for a medical imaging device. Own algorithm development from data definition and research through implementation, validation, product integration, and maintenance. Apply classical and machine learning methods to image classification, segmentation, and 3D modeling. Collaborate with software, biomedical engineering, product, and algorithm teams while improving production reliability and evaluating emerging research.

Research, develop, evaluate, and deploy AI-driven data classification capabilities using regex, rules, NER, and text classification models. Build ground-truth datasets, benchmarks, evaluation workflows, data pipelines, and dashboards to monitor precision, recall, and product quality. Analyze customer data problems, diagnose classification errors, support proofs of concept, and translate feedback into product improvements. Collaborate with the R&D Data team on AI research priorities and solutions.

Design and refine fraud decisioning logic and models for live e-commerce systems. Research fraud patterns and adversarial behavior, analyze diverse datasets, develop feature engineering solutions, and build AI-powered tools and automations. Collaborate with engineers, product managers, and business stakeholders to improve system accuracy, scalability, and efficiency.

Develop and refine fraud decisioning logic, models, and production systems for e-commerce. Research fraud patterns and adversarial behavior, analyze large-scale datasets, engineer features, and build AI-driven tools and workflows using agentic technologies. Collaborate with engineering, product, and business teams to improve system accuracy, scalability, and efficiency.

Lead product roadmap and specifications for a B2B, on-premise, AI-driven video analytics product. Define performance, scalability, and cost benchmarks for hardware-accelerated systems, collaborate with engineering, gather customer feedback worldwide, and translate technical requirements into hands-on product designs and releases.

Six-month internship focused on quantitative and machine learning research for global macro trading. Responsibilities include building data pipelines, analyzing time series and unstructured data, developing trading signals and models, applying statistical, machine learning, NLP, and LLM techniques, and creating production-quality tools to support portfolio managers.