Principal/Senior Robotics AI Architect

Job description

WHAT YOU DO AT AMD CHANGES EVERYTHING

At AMD, our mission is to build great products that accelerate next‑generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.

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)

Lighthouse Customer Co‑Engineering

Influencing Robotics Reference Architectures, Platform Architecture & SDKs

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

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

Define reference architecture for complex robotic systems (humanoids, high‑DoF manipulators, mobile manipulation platforms), establishing industry‑leading blueprints for Physical AI systems

Influence architectural 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 a bridge 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:

Reusable operator graphs and pipelines

Standardized deployment topologies

Benchmark and validation frameworks

Ensure that lighthouse customer learnings are abstracted and generalized into:

Repeatable reference architectures

Platform capabilities consumable across a wide customer base

PREFERRED EXPERIENCE:

Experience in Robotics, Autonomous systems AI architecture, definition and development, RL work, Sim‑to‑real, cloud‑to‑sim, real‑to‑sim/cloud from AI perspective.

Proven technical leadership experience influencing external and internal stakeholders.

Deep understanding of:

AI inference runtimes and deployment tradeoffs

System architecture level CPU/GPU/NPU scheduling and contention

System‑level performance, latency, and isolation

Software frameworks and usage (multimedia, ROS2, OpenCV, gstreamer, etc.)

Industry leading SW inference frameworks (vLLM, etc.), runtimes, tools

Performance bottleneck characterization

Determinism, real‑time and safety considerations in mixed‑criticality systems

Ability to engage credibly with customers’ engineering leaders and AI architects.

Track record of transforming customer deployments into platform and roadmap feedback.

Hands‑on architect who can guide engineers, debug problems, create innovative PoCs as well as abstract unnecessary details for executive presentations.

Familiarity/experience with AMD GPU and NPU AI SW stacks and tools will be a plus.

ACADEMIC CREDENTIALS:

Bachelor’s or Master’s in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field.

This role is not eligible for visa sponsorship.

Benefits offered are described: AMD benefits at a glance

AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third‑party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants' needs under the respective laws throughout all stages of the recruitment and selection process.

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.

This posting is for an existing vacancy.

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Worksite address

san jose, CA, 95199, US

Who can apply

Review the original listing for work authorization, qualifications and employer requirements.