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About This Role
- The Role and Impact This role serves as the authoritative systems architect owning the end-to-end hierarchical stack for next-generation humanoid robots.
- Acting as the critical interface between large-scale vision-language-action (VLA) models and physical platforms, this senior leader defines hierarchical multi-system architecture requirements and drives the co-optimization of advanced AI models with physical hardware under tight power, thermal, latency, and memory-bandwidth constraints.
- Key Responsibilities Humanoid Robotic System Architecture Ownership: Own the canonical hierarchical control stack, including VLM/VLA systems, visuomotor policies, whole-body control, and distributed joint FOC loops.
- You will also establish rate boundaries, latency budgets, action-chunking strategies, and select interconnect topologies (e.g., EtherCAT).
- AI Model Optimization for Silicon: Drive co-optimization of large VLA/world models with compute silicon.
- Define quantization, sparsity/MoE, context lengths, and reference deployment envelopes to align model workloads with silicon capabilities.
- Co-Optimized Model + Hardware Architecture: Perform first-principles sizing of FLOPs, sustained TOPS, and memory-bandwidth floors.
- Select optimal compute platforms and design strategic splits of AI workloads between central compute nodes and remote sensor pods.
- Key Deliverables with Cross-Functional Impact Technical Leadership and Specifications: Author and maintain primary system-level specifications (compute, power, thermal, sensors, actuator networks, safety islands) and translate high-level product goals into actionable, quantitative requirements.
- Guide evolution of relevant technology roadmaps from current baselines to future system concepts that would influence product definition.
- Cross-Functional Authority: Lead multi-disciplinary architecture reviews, key decisions, and subsystem design trades across ML research, controls, electrical, firmware, and mechanical teams.
- Collaborative Experimentation and Mentorship: Formulate and guide expert-led viability experiments.
- Mentor senior engineers in system-level thinking, addressing critical hardware barriers like the memory and power walls, and represent the platform architecture with key external silicon and actuator partners.
- Architectural Expertise: Proven ownership of architectures bridging high-level AI models with real-time hardware control, alongside deep fluency in transformer inference constraints (quantization, action chunking, memory bandwidth walls) and real-time distributed systems (EtherCAT, zonal sensor pods, safety islands).
- Exceptional technical communication with a track record of writing rigorous, quantitative system specs and driving alignment across diverse engineering domains.
Requirements
- Core Experience: 10+ years in complex cyber-physical systems, with 4-5 years specializing in robotics, autonomous systems, or high-performance edge AI platforms.
- BS in Engineering, Computer Science, Math, or related field is required.
- Preferred Assets: Direct experience with humanoid robots/mobile manipulators, hands-on exposure to VLA/foundation models (-series, Helix-class, GR00T, OpenVLA, or equivalent), expertise with robotics platforms (NVIDIA Jetson / IGX platforms, custom AI silicon, or both), and battery/thermal budgeting for highly constrained systems.
- Join us in this exciting opportunity to lead the innovation and development of transformative platforms that set industry benchmarks and drive Intel's vision for next-generation computing experiences.
Benefits
- We offer a total compensation package that ranks among the best in the industry.
- It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation.
- Find out more about the benefits of working at Intel .
- Annual Salary Range for jobs which could be performed in the US: $220,920.00-361,480.00 USD The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations.
- Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
- Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.
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614 positions
Job ID
/job/US-Oregon-Hillsboro/Lead-Humanoid-Robotics-System-Architect_JR0286633
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