Principal​/Senior Robotics AI Architect

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THE ROLE:

We are seeking a Robotics AI Architect to define and scale next-generation Physical AI systems, with a focus on complex robotic platforms (including humanoids). This role emphasizes architectural leadership across multi-layer AI control loops and tight collaboration with lighthouse customers to achieve production-grade performance targets.

THE PERSON:

As a key technical authority, you will synthesize learnings from real-world deployments and translate them into platform-defining capabilities, shaping the roadmap for our AI SDKs, runtime, and reference architectures to enable broad ecosystem scalability.

KEY RESPONSIBILITIES:

End-to-End AI Control Loop Architecture (Core Focus)
Define architecture for hierarchical AI control loops, including:

Perception (sensor fusion, VLMs, state estimation)
World modeling and scene understanding

Task and motion planning

Low-latency control and actuation

Learning and adaptation loops

Establish timing models and system-level constraints:

Deterministic execution for control loops (µs–ms)
Bounded latency for perception/planning (ms-scale)
Guide architectural decisions to:

Minimize latency, jitter, and data movement

Optimize compute utilization across heterogeneous systems

Influence compute-software co-design across CPU, GPU, and accelerators

Lighthouse Customer Co‑Engineering Act as architectural lead for strategic/lighthouse customers, guiding:

System design decisions

Performance trade-offs Deployment architecture

Influence customer implementations to align with:

Platform best practices

Scalable architectural patterns

Translate real-world constraints (latency, power, safety) into:

Platform requirements

Architecture refinements

Lead deep technical engagements, including:

Architecture and design reviews

Performance tuning strategies

System-level debugging approaches

Influencing Robotics Reference Architectures, Platform Architecture & SDKs  Define reference architecture for complex robotic systems (humanoids, high-DoF manipulators, mobile manipulation platforms), establishing industry-leading blueprints for Physical AI systems

Influencearchitectural partitioning strategies across:

On-robot compute (real-time loops)
Edge/accelerator subsystems

Cloud (training, simulation, fleet learning)
Provide architectural guidance on:

Whole-body control integration

Locomotion and balance systems

Dexterous manipulation pipelines

Multi-modal perception stacks

Serve as abridge between lighthouse deployments and platform evolution, translating system-level insights into:

SDK feature direction

Runtime and middleware enhancements

Reference pipeline abstractions

Shape the roadmap of:

Physical AI SDK and runtime frameworks

Robotics middleware integrations (ROS2 and beyond)
Dataflow and scheduling architectures for deterministic execution

Identify systemic gaps and influence solutions in:

Scheduling and orchestration models

Memory and dataflow efficiency

Inter-process/inter-node communication

Real-time guarantees and QoS mechanisms

Drive the creation of scalable architectural patterns, including:

Reusa…