greenhouse
Staff AI Inference and Acceleration Engineer
Figure
Napi Headquarters, USA
Senior · 8+ years experience
USD 180000-275000 / year
Discovered 1 weeks ago
cplusplusjaxpython
Free
Job Fit Check
Base Career helps you apply smarter for this job.
?%
Ready to ScanKey skills for this role
cplusplusjaxpython
Key Skills for This Role
cplusplusjaxpython
Full Job Posting
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.
Apply for this job in 1 click
Skip the repetitive application forms
Install the Base Career Chrome Extension and autofill job applications across major job boards with your profile.
Trusted by over 500,000 job seekers on Base Career
More from this employer
More jobs at Figure
Software Engineer, Service & Operations
San Jose, USA
Discovered Today
Production Lead (Swing Shift)
San Jose, USA
Discovered Yesterday
Special Projects Intern [Fall 2026]
San Jose, USA
Discovered Yesterday
Senior Marketing Manager, ABM
, USA
Discovered 1 weeks agoFull-time
Deployment Logistics Coordinator
San Jose, USA
Discovered 1 weeks agoFull-time
Logistics & Dispatch Coordinator
San Jose, USA
Discovered 1 weeks agoFull-time
Helix AI Engineer, Data Infrastructure
Napi Headquarters, USA
Discovered 1 weeks ago
Project Lead, Data Creators (CDMX)
Mexico, USA
Discovered 1 weeks ago
