Top Machine Learning Jobs in Israel

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

Develop and maintain NetSuite customizations, SuiteScripts, workflows, and PDF templates. Build Workato integrations and API-driven automations across Finance, Procurement, Legal, and other teams. Optimize business processes, develop AI-powered workflow tools, support anomaly detection and predictive insights, and maintain data integrity, security, governance, and audit readiness across financial systems.

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 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.

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.

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).

Serve as the technical lead for fraud prevention, building AI/LLM agents, ML and graph-based detection models, conducting expert forensic investigations, and partnering cross-functionally to embed scalable, real-time fraud defenses using Python, SQL, and advanced data infrastructure.

Lead a Core Product engineering group in Tel Aviv, managing engineering managers and multiple teams. Drive delivery, quality, and AI-embedded product initiatives; partner with Product, Design, Data, and GTM to shape roadmap, resolve dependencies, improve cross-team collaboration, and scale hiring and org design.

As a Senior Data Scientist, you will build NLP and ML models, lead projects, and drive data science solutions across B2B and B2C domains at Lightricks.

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.

Lead the strategy, roadmap, discovery, growth, and monetization of Viber Dating, a scalable B2C mobile product. Drive user research, prototypes, experimentation, KPI-based decisions, and cross-functional alignment with executives, design, engineering, analytics, marketing, and Trust & Safety. Translate complex machine-learning concepts into clear product direction, launch 0-to-1 experiences, mentor product teams, and improve authentic user connections.

Develop, implement, evaluate, and improve computer vision algorithms for 3D point-cloud processing using classical and machine-learning methods. Work with proprietary LiDAR data to deliver innovative, state-of-the-art solutions for autonomous vehicles and other applications. Collaborate closely with a technical team while designing algorithms, developing software, and potentially optimizing implementations for embedded platforms.

Owns end-to-end planning, coordination, and delivery of a complex NPU AI software stack spanning compilers, runtimes, SDKs, drivers, and firmware. The role synchronizes software, validation, and architecture teams; manages risks, dependencies, milestones, customer commitments, and release readiness; and establishes SDLC quality gates and post-mortem processes. Success requires technical software engineering depth, strong cross-functional leadership, and the ability to drive accountability across distributed teams without direct authority.

Lead development and execution of AI-driven AML products. Define strategy, roadmap, and requirements; work with engineering, data science, and design; engage customers and stakeholders; apply ML and analytics to improve detection; track KPIs and iterate on product performance.

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.

Supports the development of scalable data pipelines, data models, warehouses, semantic layers, dashboards, and analytics solutions using Python and SQL. Monitors data quality, troubleshoots workflows, documents data systems, and contributes to orchestration, testing, automation, and platform reliability. Collaborates with business and technical teams across rotating domains while exploring AI-assisted engineering and Generative AI applications. This early-career role includes mentorship, Agile participation, and increasing project ownership.

Design, implement, test, debug, and optimize signal-processing algorithms that convert field sensor data into accurate 3D underground maps. Translate mathematical models and research into production code, validate results against ground truth, collaborate with algorithm, systems, and field teams, and develop deep knowledge of sensor operation. The role requires independent learning, ownership, analytical thinking, and effective communication in a multidisciplinary environment.

Leads global weekly capacity planning for NVIDIA Boards & Systems manufacturing. Responsibilities include consolidating forecasts and supply inputs, analyzing capacity constraints, performing scenario modeling, optimizing contract manufacturer loading, rationalizing capital investments, coordinating global cross-functional teams, integrating planning tools and data pipelines, and presenting execution and risk-mitigation strategies to senior management.

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.

Design and develop scalable, high-performance distributed software platforms for semiconductor inspection and diagnostics systems. Build services running on Linux and Kubernetes, lead architecture and technical decisions, deliver complex features from design through production, and optimize performance, reliability, and maintainability. Collaborate with software, algorithms, systems, and architecture teams while evaluating AI-generated solutions and applying strong engineering judgment.

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.

Perform deep-dive quantitative analyses, evaluate ML models and A/B tests, design experiments, define metrics, forecast and segment user behavior, and translate findings into product recommendations and stakeholder presentations.

As a Senior Data Scientist, you will develop classification and anomaly detection algorithms using machine learning and statistical methods while collaborating across teams to enhance data-driven products for small businesses.

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.