What We’re Looking for:

We are looking for people who are passionate about delivering self-driving (L4) products that make the way we move safer, faster, and more efficient. We seek mission-driven, highly skilled people with deep experience in fast-paced, rapidly growing, tech development environments.

The prediction team is responsible for consuming tracks, track history, track attributes, environmental signals, maps, and any other scene context, and creating probabilistic predictions of future actions as well as semantic categorization and intent estimation. We make extensive use of our road-collected dataset to train the best possible machine learning models and produce signals to help planner make safe, comfortable driving decisions on the road.

What Success Looks Like:

• Be part of a team of engineers to develop state-of-the-art prediction & planning ML modules for self-driving vehicle systems.
• Own delivery of prediction or planning ML modules that solve on-vehicle problems and deliver for customer needs - meeting product requirements and meeting the needs of downstream components, providing accurate, timely prediction signals to inform driving behavior.
• Provide input in the technical direction for the team, and work cross-functionally to develop safe systems.  This will include working closely with other teams such as perception, planning, and machine-learning infrastructure to ensure seamless integration and maximum efficiency.
• Work closely with systems engineers to ensure a safe, well-tested product is delivered.
• Work closely with verification teams to ensure proper testing and validation of the prediction modules.  Make extensive use of unit testing, simulation, and log simulation to properly validate their work.
• Provide input to team roadmaps and ensure product features are properly prioritized.
• Develop prediction and planning ML models for real-time, resource-constrained applications.
• Identify bottlenecks and limitations in system performance, and develop novel prediction and planning ML components to unlock new capabilities and ensure a reliable system.
• Be involved in experimentation, design, and iteration exercises, and help align stakeholders by using strong presentation and communication skills.
• Strong experience in software engineering and algorithm design.
• Knowledge and experience with real-time algorithms and machine learning approaches.
• Experience architecting, training, and deploying machine-learned models, or designing machine-learning systems and infrastructure.
• Experience building perception, prediction, or planning systems for real-world applications with a strong understanding of the pros and cons of various approaches.
• Fluent in C++.
• Experience with Python or CUDA a plus.