What to Expect

As a member of the Self-Driving team, you will take on a highly cross-functional role to automatically label large amounts of data from the global Tesla vehicle fleet, train cutting-edge deep neural networks on these labels, and integrate the models with the rest of the Self-Driving software stack to support numerous state-of-the-art autonomous driving functionalities and safety-critical features.

We are looking for both generalists with a breadth of expertise who are excited to work across the entire pipeline, as well as specialists who can dive deep on specific modules.

What You’ll Do
Develop offline state estimation, 3D reconstruction, and sensor fusion algorithms to automatically generate supervision for deep neural networks
Train deep neural networks with large scale, auto-labelled datasets
Design and implement tools, tests, and metrics to accelerate the data generation and model development cycles
Integrate the models with the real-time embedded C++ software stack
Work with planning & controls team to develop control policies on top of network outputs
What You’ll Bring
Minimum 3 years of experience writing production-level Python or C++
Strong mathematical fundamentals including linear algebra, vector calculus, probability theory, and numerical optimization
Exposure to a major deep learning framework such as PyTorch, TensorFlow, Keras, or MXNet
Prior work in robotics, state estimation, visual odometry, SLAM, structure from otion, or 3D reconstruction
Exposure to recent advances in differentiable rendering and neural rendering techniques is a plus

Palo Alto, California

Full time