3 months ago
San Jose, CA, USAStaff+
Base Salary
$180k - $275k/yr
Responsibilities
- Own the on-board inference architecture and map models to available NPU, GPU, DSP, and CPU resources based on latency, power, and memory budgets.
- Partition inference workloads across heterogeneous compute resources while balancing real-time performance, power, and thermal constraints.
- Define and maintain a system-level compute budget for all inference tasks running on the robot.
- Evaluate next-generation acceleration hardware and help define future compute platform requirements.
- Optimize inference toolchains from model export through runtime execution for target hardware.
- Apply quantization, pruning, operator fusion, and other compression techniques to reduce compute, memory, and power usage.
- Profile inference pipelines and optimize kernel scheduling, memory layout, and data movement.
- Collaborate with AI/ML and Platform Software teams on hardware-friendly model architectures, runtime integration, scheduling, and power management.
- Engage with silicon vendors and research teams to track accelerator developments and influence hardware roadmaps.
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.
- Deep understanding of AI/ML inference, model formats, 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, including memory hierarchies, data movement, and heterogeneous compute.
- Experience profiling and benchmarking inference workloads across CPU, GPU, NPU, and DSP.
- Familiarity with low-level toolchains and compilation frameworks including TVM, MLIR, TensorRT, Torch, SNPE/QNN, JAX, CUDA, and ROCm.
- Strong software engineering skills in C++ and Python.
- Ability to work effectively across hardware, software, and AI/ML teams.
- Knowledge of real-time operating constraints and experience co-designing model architectures with ML teams are bonus qualifications.
About Figure AI
Figure AI builds general‑purpose autonomous humanoid robots and the AI software that powers them, targeting tasks in industrial, commercial, and eventually residential settings. The privately held company monetizes through robotics hardware and related software/services aimed at enterprises seeking automation. Founded in 2022 and headquartered in San Jose, California, it has announced a partnership with BMW Manufacturing to pilot humanoid robots in automotive production.