Lead the research, design, and development of algorithms and ML models that enhance vehicle decision-making, expand ODDs, and ensure robustness against long-tail events and subsystem failures.
Collaborate with cross-functional engineering teams (Perception, Prediction, Hardware, Infrastructure, etc) to architect a holistic system that maximizes safety and performance at scale.
Architect dynamic simulation scenarios to validate expanded ODDs, ensuring rigorous testing of the system’s "edge case" limits.
Maintain a high bar for technical excellence by clearly documenting research findings, system architectures, and validation results to ensure organizational alignment and safety traceability.
Act as a technical catalyst by mentoring junior engineers in software craftsmanship, algorithmic rigor, and systems thinking.

Expert in robotics decision making, motion planning, and controls algorithms and ML models
Experience designing, developing, and delivering complex robotic or automation systems
Experience with robotics systems and the ability to root cause problems
Experience writing software for safety critical embedded systems utilizing C++, Rust, or similar
Experience developing analytics using Python, or similar
Experience with testing, verification, and validation of systems with functional safety requirements
Experience with simulation systems for robotics and/or autonomous vehicles
Experience using Linux operating systems, and ability to work in terminals/shells to perform troubleshooting, system performance monitoring, and kernel/journal log debugging
Experience profiling CPU, GPU, Disk, and Network usage

Principal Engineer

Key skills