Intel
Lead Humanoid Robotics System Architect
$221K–$361K
US, Oregon, Hillsboro +3 · Full-time · Posted Aug 28, 2026
- Location
- US, Oregon, Hillsboro
US, California, Folsom
US, California, Santa Clara
US, Arizona, Phoenix - Experience
- 10+ years in complex cyber-physical systems, with 4–5 years specializing in robotics, autonomous systems, or high-performance edge AI platforms.
- Education
- BS in Engineering, Computer Science, Math, or related field is required.
About the job
Architects the end-to-end humanoid robot system, integrating AI models with real-time hardware control and optimizing their joint performance within power, thermal, latency, and memory constraints.
What you'll do
- Own the hierarchical robotics control stack and set system requirements, timing budgets, and interconnect choices.
- Co-optimize AI models and compute hardware; size workloads and allocate them across compute nodes and sensor pods.
- Write system specifications, lead cross-functional architecture reviews, guide experiments, and mentor engineers.
What they ask for
- 10+ years in complex cyber-physical systems, including 4–5 years specializing in robotics, autonomous systems, or high-performance edge AI platforms.
- BS in Engineering, Computer Science, Math, or related field.
- Experience bridging high-level AI models with real-time hardware control, including transformer inference constraints and distributed systems.
- Strong technical communication and a track record of writing quantitative system specifications and aligning diverse engineering teams.
Nice to have
- Experience with humanoid robots or mobile manipulators, VLA/foundation models, or NVIDIA Jetson / IGX platforms or custom AI silicon.
- Experience with battery and thermal budgeting for constrained systems.
Pay
$220,920.00-361,480.00 USD (target compensation; base salary or total pay not specified)
Tools
VLM/VLA, EtherCAT, NVIDIA Jetson, IGX, GR00T, OpenVLA
AI focus
Co-optimize large VLA/world models with compute silicon, including defining quantization, sparsity/MoE, context lengths, and deployment envelopes.
Model-written summary · the original posting is authoritative