Own design and development of ML models or model components for end-to-end autonomous driving: ranging from initial data strategy, design, development, experimentation, evaluation and deployment.
Resolve ambiguities and address uncertainties arising from complex projects involving multiple teams and legacy codebases.
Enable and help other colleagues on the team to be more effective through leading by example when it comes to writing high-quality code, being rigorous with Machine Learning experimentation and knowledge sharing.
Collaborate closely with stakeholders from multiple teams in different time-zones to define interfaces and requirements for an end-to-end stack.
Requirements
MS, or higher degree, in related field, or equivalent industry experience
Professional experience with ML frameworks such as PyTorch, Jax or Tensorflow (PyTorch preferred)
Knowledge of debugging and profiling deep neural networks on NVIDIA CUDA stack
Experience in state of the art architectures for object detection and 3D perception
Experience in ML workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization
Python and C++ experience
Hands-on experience with building a perception stack for autonomous systems
Familiarity with recent breakthroughs in ML (e.g. foundation models, pre-training and efficient fine-tuning, multimodal Transformer architectures)
Hands-on experience with large scale distributed training
Benefits
Excellent health, wellness, dental and vision coverage
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