Staff Ai Software Engineer, Edge Model Optimization & Deployment

FieldAI

Seattle, WA, United States
On-site
Optimize ml models on robotic platforms
Drive edge inference stack end to end
Improve runtime performance (latency, throughput, memory, power)
Our growing ML team in Seattle builds risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence

Job Summary

  • Our growing ML team in Seattle builds risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence.
  • In this role, you will own the edge inference stack end to end, profiling and accelerating models, improving runtime performance across latency, throughput, memory, and power, and partnering closely with perception, autonomy, and platform teams to deliver robust on-robot behavior in the field.
  • This is an opportunity to shape the future of robotic autonomy by translating state-of-the-art ML into high-performance, production-grade edge deployments that operate reliably in complex, dynamic environments on real robots.

Matching Summary

Our growing ML team in Seattle builds risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence.

Skills & Requirements

Must-have

  • optimize ML models on robotic platforms
  • drive edge inference stack end to end
  • improve runtime performance (latency, throughput, memory, power)
  • partner with perception, autonomy, and platform teams
  • set technical direction for edge deployments

Nice-to-have

  • pragmatic approach beyond off-the-shelf methods
  • combining cutting-edge research with real-world deployment
  • continuous improvement driven by field use

Key Requirements

  • accomplished Staff AI Software Engineer

Work Rights

Not specified

Tailored Resume

Cover Letter