Staff AI Inference and Acceleration Engineer

Job summary

Responsibilities

We are looking for a Staff AI Inference & Acceleration Engineer to join the Platform Software team and own the on-board inference architecture for Figure’s humanoid robots. You will be the technical authority on how AI workloads are mapped, optimized, and executed across the robot’s compute…

• Own the on-board inference architecture — mapping models to available accelerators (NPU, GPU, DSP, CPU) based on latency, power, and memory budgets.
• Partition inference workloads across heterogeneous compute resources, balancing real-time performance with power and thermal constraints.
• Define and maintain a system-level compute budget across all inference tasks running on the robot.
• Evaluate next-generation acceleration hardware and contribute to the definition of future compute platform requirements.
• Optimize inference toolchains end-to-end — from model export through runtime execution — for target hardware.

What they're looking for

• 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.
• Deep understanding of AI/ML inference — model formats (ONNX, TFLite, etc.), inference runtimes, and deployment pipelines.
• Hands-on experience optimizing models for edge or embedded hardware using quantization, pruning, and operator-level tuning.
• Strong understanding of computer architecture — memory hierarchies, data movement, and heterogeneous compute.

Tech stack

• JAX
• CUDA
• C++
• Python