Technical Project Manager

A globally recognized Semiconductor & Software leader at the forefront of wireless communication, smart sensing, and artificial intelligence.

The company’s AI Division is a world-class innovation hub, architecting the future of Generative AI and Machine Learning for edge devices and cloud inference.

With a focus on high-performance Neural Network Processors (NPU) and Vision DSPs, the organization delivers cutting-edge IP and system-level solutions to the world’s leading SoC makers and OEMs.

Located in Central Israel (adjacent to major transit hubs), the company fosters an elite R&D culture with a hybrid work model (2 days WFH).

Responsibilities

• Executive Matrix Leadership: Leading high-caliber teams across Architecture, Algorithms, VLSI, and Embedded Software, ensuring seamless synchronization toward product goals.
• E2E Lifecycle Ownership: Driving the full product lifecycle from initial concept and PRD definition through architecture and R&D, to mass production-ready delivery.
• AI Ecosystem Orchestration: Managing the intricate synergy between Data Science, Graph Compilers, Simulation Architecture, and Hardware design within the NPU domain.
• Global Strategic Interface: Serving as the primary technical and operational bridge between global Tier-1 customers, Product management, and R&D squads.
• Program Execution & Governance: Leading program planning, risk mitigation, and quality assurance using metrics-driven methodologies to ensure world-class delivery standards.

Requirements-

• B.Sc. in Electrical Engineering or Computer Science – Mandatory.
• 10 years of leadership experience within the Semiconductor industry – Mandatory.
• 5 years managing complex, large-scale HW/SW R&D projects – Mandatory.
• Proven experience in leading R&D programs for Neural Network Processors (NPU) or high-end AI accelerators – Mandatory.
• Demonstrated success in leading a product from concept to Mass Production within a global organizational framework.
• Expertise in advanced project management methodologies, planning tools, and data-driven execution.