Machine Learning Engineer Job at Tesla
What to Expect
What You’ll Bring
You will be part of a small team of deep learning experts, working in tandem with Autopilot AI neural network task owners, to train powerful foundation models that encode features relevant to autonomous driving and understanding of the world.
What You’ll Do- Train large generative models and multi-task networks that deeply understand the world and how it evolves over time, with the end goal of benefitting downstream tasks involving autonomous perception and planning
- Push the boundaries of machine learning in the autonomous driving industry by developing cutting-edge techniques in multi-task learning, video networks, generative models (e.g., diffusion, VQ-VAE, autoregressive transformers), and semi-supervised methods (e.g., DINO).
- A track record of training large, complex models successfully, from dealing with infra issues and stabilizing large model training, to techniques for balancing multi-task learning and training high-quality generative models
- Strong experience with Python and software engineering best practices.
- An “under the hood” knowledge of deep learning: layer details, loss functions, optimization, etc.
- Fluency with common neural network architectures for computer vision, speech, NLP, etc.
- Experience with PyTorch, or another major deep learning framework such as JAX or TensorFlow.
- Familiarity with standard scientific computing primitives, such as batched operations, grid-sample, scatter / gather, einsum, etc.
- (bonus) Strong systems knowledge, ability to profile and optimize training and evaluation scripts
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