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About
Develop and train machine learning models for acquired behavior systems using techniques like behavior cloning and reinforcement learning Implement production-quality code to support training, evaluation, and inference of models within the autonomy stack Analyze model performance, identify failure modes, and propose improvements to enhance robustness across various scenarios
Required Qualifications
Bachelor's degree in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a related technical field with at least 4 years of experience, or a Master's degree with at least 2 years of experience Experience applying machine learning techniques such as imitation learning, reinforcement learning, or sequence modeling in autonomous systems or complex control environments Strong programming skills in Python and PyTorch, with experience in production-quality machine learning coding Experience training and evaluating machine learning models using large datasets and adaptive computing environments Understanding of machine learning architectures used in autonomous driving systems, such as transformers and graphical neural networks
Languages
- English
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