Machine Learning Engineer, Destination & Special Behaviors, Self-Driving

Tesla is looking for an experienced applied Machine Learning Engineers to help build models that deliver robust for robotics to drive the future of autonomy across all current and future generations of vehicles. You will work on a lean team without boundaries and have access to one of the world’s largest training clusters. Most importantly, you will see your work repeatedly shipped to and utilized by millions of Tesla’s customers.

Responsibilities

Work on developing novel techniques for robustly handling start and end of trip Robotaxi behaviors in a rapidly scalable way Leverage millions of miles of driving data and interventions to build a robust and scalable end-to-end learning based self-driving system Use cutting-edge techniques from generative modeling, imitation learning, and reinforcement learning to improve the planning and reasoning capabilities of our driving models Work cross-functionally across ground truth generation, ML model training, and on-vehicle deployment Experiment with data generation and fleet data collection approaches to enhance the diversity and quality of training data Integrate directly with vehicle firmware and ship production quality, safety-critical software to the entirety of Tesla's vehicle fleet

Requirements

Strong experience with Python, any major deep learning framework, and software engineering best practices An "under the hood" knowledge of deep learning modern architectures, optimization, model alignment, etc. Proven expertise in deploying production ML models for self-driving and robotics at scale Any experience with C++ would help integrate with vehicle firmware and take projects from ideas to shipped products