Lead Humanoid Robotics System Architect

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.

Minimum Qualifications:

• 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.