About The Role We're supporting our client who is building next-generation humanoid robots from the ground up - custom silicon, actuators, and the AI stack that runs on them. This role sits at the intersection of hardware and AI, where your decisions directly shape what the robot can perceive and do at the edge.

What You'll Do

• Design and develop custom AI inference hardware to run neural networks on-robot with maximum performance-per-watt
• Architect and validate hardware components powering perception, locomotion, and manipulation pipelines
• Collaborate with ML and firmware teams to co-design silicon architecture that meets real-time robotics constraints
• Perform floor-planning, timing, and power analyses across the hardware design stack
• Write robust verification tests and scoreboards to validate functionality and performance
• Implement low-level drivers and communication interfaces focused on performance optimization and fault tolerance
• Drive hardware bring-up and field debugging across prototypes through production

What You'll Bring

• BS/MS/PhD in Electrical Engineering, Computer Engineering, or related field
• 5+ years of experience in AI/ML accelerator or embedded systems hardware design
• Proficiency in RTL design (Verilog / SystemVerilog) and hardware verification methodologies
• Familiarity with deploying neural networks on custom or edge accelerators
• Strong understanding of performance-power trade-offs in constrained compute environments
• Experience with sensor integration (cameras, IMUs, proprioception) preferred
• Prior work on robotics, autonomous vehicles, or embedded AI hardware is a strong plus