Advanced Micro Devices, Inc

Senior Level Robotics AI Architect

Advanced Micro Devices, Inc • $150K — $200K *
San Jose, CA 95123In-Person
Consumer Technology
15+ years of experience
2 weeks ago
Job Overview by Ladders

Qualifications

  • 17+ years of experience in Robotics and Autonomous Systems AI architecture.
  • Proven technical leadership with a focus on external and internal stakeholder influence.
  • Deep understanding of AI inference runtimes and deployment trade-offs.
  • Expertise in system architecture level CPU/GPU/NPU scheduling and contention.
  • Hands-on experience in transforming customer deployments into impactful platforms.

Responsibilities

  • Define architecture for hierarchical AI control loops, including perception and task planning.
  • Establish system-level constraints for deterministic execution and bounded latency for perception/planning.
  • Guide decisions to minimize latency, jitter, and optimize compute utilization across systems.
  • Act as architectural lead for strategic customers, guiding system design and deployment architecture.
  • Translate real-world constraints into platform requirements and architecture refinements.
  • Define reference architecture for complex robotic systems, establishing industry-leading blueprints.
  • Identify systemic gaps and influence solutions in scheduling, dataflow efficiency, and real-time guarantees.

Benefits

  • Comprehensive AMD benefits including health, retirement, and wellness programs.
Full Job Description
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:
  1. 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


  1. 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


  1. 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
  • 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:
  • 17+ years of 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 customer's engineering leaders, AI architects
  • Track record of transforming customer deployments into platform and roadmap feedback
  • Hands-on architects 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 Engineer, Computer Engineering, Computer Science, or a closely related field


This role is not eligible for visa sponsorship.

#LI-MH2

Benefits offered are described: AMD benefits at a glance.

About Advanced Micro Devices, Inc

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Learn more about Advanced Micro Devices, Inc
Size
15,500 employees
Market Cap
$100.9 billion
Industry
Manufacturing & Automotive
Net Income
$2.4 billion
Founded
1969
5 Year Trend
+30.9%
Revenue
$9.7 billion
NASDAQ
AMD
* Ladders Estimates

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