Leverage millions of miles of driving data and interventions to build a robust and scalable end-to-end learning based self-driving system
Research on cutting-edge techniques in multi-modal generative models, reward models and reinforcement learning to improve the planning and reasoning capabilities of our driving models
Experiment with data generation and network driven data collection approaches to enhance the diversity and quality of training data
Ship production quality, safety-critical software to the entirety of Tesla’s vehicle fleet
What You’ll Bring
Strong experience with Python and software engineering best practices
Experience with Pytorch or another major deep learning framework
An “under the hood” knowledge of deep learning: layer details, loss functions, optimization, etc.
Proven expertise in deploying production ML models for self-driving, computer vision, or natural language processing at scale
Experience with imitation learning, reinforcement learning (offline/off-policy), modern neural network architectures (e.g., GPT, diffusion), or related techniques