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Lead and develop a team of Systems Analysts while owning end-to-end analysis, specification quality, and delivery support across complex integrated systems.

Lead advanced product analytics and data science initiatives that guide product strategy, experimentation, forecasting, and investment decisions across large-scale consumer applications. Partner with Product, Engineering, Research, and executive stakeholders to turn behavioral data into actionable,,

Join a cloud infrastructure engineering team developing software and networking capabilities for large-scale computing systems. This part-time role requires availability for two to three workdays per week and at least two semesters remaining before graduation.

Join an internal system product engineering team validating software infrastructure used across the organization. Own test coverage, automation, debugging, and quality improvements for backend services, data pipelines, internal tools, and workflows.

Join an automotive technology company developing production systems that bridge machine learning research and reliable, scalable deployment.

An imaging technology research team in Tel Aviv is seeking an algorithm engineer to develop and productize deep learning solutions for computer vision and image processing. The role works closely with hardware and software architects and requires at least three days per week in the office.

Join a multidisciplinary systems team in the defense sector, developing automated tests for integrated software and hardware systems.

Join an internal engineering team developing tools for next-generation CPU validation. This part-time, on-site internship is based in Haifa, Israel, and is intended for Computer Science or Software Engineering students.

Lead technical research and end-to-end delivery for applied data science projects at a healthcare AI company. Own modeling strategy, client delivery, GenAI workflows, and reusable team tooling while remaining a hands-on senior individual contributor.

Join an automotive technology team developing robust production systems that bridge machine learning research and scalable deployment. The role focuses on Python-based infrastructure, inference pipelines, and modern MLOps practices.