Machine Learning Engineer

The local R&D center of a successful multinational semiconductor and hardware systems enterprise. The company develops high-performance silicon, advanced storage architectures, and smart connectivity chipsets deployed in billions of consumer and enterprise devices worldwide.

The site operates as a core innovation hub, combining the robust backing of a global tech leader with deep-tech R&D challenges.

Located in the Tel Aviv area with excellent public transit and train accessibility, operating under a flexible hybrid work model (including WFH options).

Position Overview-

• Senior Machine Learning Researcher & Algorithm Engineer joining a core ML group focused on next-generation storage systems, security, and hardware reliability.
• Owning the full research and development lifecycle: from problem formulation and heavy data collection to algorithmic design, proof-of-concept validation, and production deployment at scale.
• Designing and implementing predictive ML models tailored for high-frequency time-series and tabular telemetry data generated by hardware components.
• Partnering closely with Hardware Designers, Firmware Engineers, and System Architects to integrate intelligent software models directly into next-generation silicon frameworks.
• Contributing to the company's intellectual property through technical reports, patent applications, and research publications where applicable.
• Integrating advanced AI productivity tools and software agents into the research and engineering workflow to optimize debugging, code generation, and technical documentation.
• Core Domain & Ecosystem- Machine Learning Research, Applied AI, Storage Security & Reliability, Time-Series & Tabular Data, Hardware-Software Co-design, Python, PyTorch, AI Agents / Productivity Utilities, Silicon Systems Lifecycle.

Requirements-

• Academic Background: M.Sc. or Ph.D. in Computer Science, Electrical Engineering, Data Science, or a closely related quantitative field – Mandatory
• 5+ years of robust professional experience designing, developing, and deploying machine learning algorithms inside production-grade environments – Mandatory
• Extensive, practical experience building and optimizing ML models specifically for time-series analysis and tabular datasets – Mandatory
• Production-grade programming mastery in Python alongside deep framework hands-on experience with PyTorch – Mandatory
• Demonstrated hands-on experience utilizing AI-assisted engineering utilities, LLM workflows, or AI agents to accelerate software development, debugging, and research documentation – Mandatory
• Strong system-level understanding with the ability to bridge the gap between abstract mathematical research and low-level hardware constraints – Mandatory
• Excellent technical writing capabilities, with a proven background or strong readiness to author patents and research publications – Mandatory