Principal Machine Learning Engineer

What you'll do

• Develop autonomy algorithms and foundation models to extract high-fidelity semantic meaning from complex urban edge cases.
• Design state-of-the-art multi-modal models to interpret the causality behind ego vehicle behaviors in logged data.
• Create a comprehensive, structured taxonomy for the autonomous database to power advanced data mining.
• Architect the intelligence behind the L4 data and evaluation engine to improve data mining and scene understanding.
• Set the technical direction for machine learning systems that process massive amounts of real-world driving data.
• Mentor senior and lead engineers while fostering a culture of rigorous experimentation and engineering excellence.
• Act as a bridge between internal teams to ensure semantic models and platforms are integrated at scale.

What we're looking for

• 10+ years of experience in the ML, Robotics, or Autonomous Systems industry.
• Proven experience leading large-scale technical projects from conception to production.
• Bachelor's degree in Computer Science, Computer Engineering, or related fields.
• Expert-level proficiency in Python and Linux environments.
• Deep expertise in modern AI/ML frameworks such as PyTorch or TensorFlow.
• PhD in Robotics or Machine Learning with a focus on Autonomous Driving, Computer Vision, or foundation models (preferred).
• Extensive experience with C++, CUDA, and high-performance system optimization for massive offline datasets (preferred).
• Experience building and scaling "Foundation Models" for physical world interaction, scene representation, or causal behavior modeling (preferred).