Figure

Figure

Staff AI Inference and Acceleration Engineer

San Jose, CA · Staff+ · Full-time

Sponsorship not specified$180k-$275kDetected 25 days ago
C++Machine LearningRoboticsElectrical EngineeringSignal ProcessingResearchCommunication

About the role

  • The goal of the company is to ship humanoid robots with human level intelligence.
  • Figure is headquartered in San Jose, CA.
  • The US base salary range for this full-time position is between $180,000 - $275,000 annually.

Responsibilities

  • Own the on-board inference architecture - mapping models to available accelerators (NPU, GPU, DSP, CPU) based on latency, power, and memory budgets.
  • Define and maintain a system-level compute budget across all inference tasks running on the robot.
  • Optimize inference toolchains end-to-end - from model export through runtime execution - for target hardware.
  • Optimize kernel scheduling, memory layout, and data movement across the compute hierarchy.
  • Partner closely with the AI/ML team to define model architecture constraints that are hardware-friendly from the outset.
  • Figure is an AI robotics company developing autonomous general-purpose humanoid robots.
  • Its robots are engineered to perform a variety of tasks in the home and commercial markets.

Requirements

  • M.S. or Ph.D. in Computer Engineering, Electrical Engineering, Computer Science, or a related field - or equivalent industry experience.
  • At least 8 years of industry experience in hardware acceleration, ML systems, or compute architecture.
  • Strong understanding of computer architecture - memory hierarchies, data movement, and heterogeneous compute.
  • Experience profiling and benchmarking inference workloads across CPU, GPU, NPU, DSP.
  • Familiarity with low-level toolchains and compilation frameworks (e.g. TVM, MLIR, TensorRT, Torch, SNPE/QNN, JAX, CUDA, ROCm).

Nice to have

  • Knowledge of real-time operating constraints and their impact on inference scheduling.
  • Track record of co-designing model architectures with ML teams to meet hardware constraints.
  • The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience.
  • This information will be shared if an employment offer is extended.

Compensation

  • The US base salary range for this full-time position is between $180,000 - $275,000 annually.
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