Jobs / United States / Figure AI INC
Staff AI Inference and Acceleration Engineer
Figure AI INC · 🇺🇸 San Jose, CA
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 22 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 1 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Figure AI INC paid sponsored hires in similar roles3 certified filings for “AI TRAINING INFRASTRUCTURE ENGINEER” (Software Developers) in CA: $200k–$227k, median $225k. Most were filed at wage level II (67%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
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Sponsor Radar — Figure AI INC
The US Department of Labor certified 22 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 1 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Figure AI INC →
About the role
Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of the company is to ship humanoid robots with human level intelligence. Its robots are engineered to perform a variety of tasks in the home and commercial markets. Figure is headquartered in San Jose, CA. 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 hardware — driving down power consumption and cost while meeting the strict latency and reliability demands of a real-time autonomous system. Responsibilities: • 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. • Apply quantization (INT8, INT4, mixed-precision), pruning, operator fusion, and other compression techniques to reduce compute, memory, and power footprint. • Profile inference pipelines to identify and eliminate bottlenecks in latency, memory bandwidth, and power consumption. • 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. • Work with the Platform Software team on runtime integration, scheduling, and power management. • Engage with silicon vendors and research teams to track the accelerator landscape 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 (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. • 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). • Solid software engineering skills in C++ and Python. • Strong cross-functional communication skills — able to work effectively across hardware, software, and AI/ML teams. Bonus Qualifications: • 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 US base salary range for this full-time position is $180,000 to $275,000 per year. The pay offered for this position may vary based on several individual factors, including job-related knowledge, skills, and experience. The total compensation package may also include additional components/benefits depending on the specific role. This information will be shared if an employment offer is extended.