Senior/Staff Machine Learning Engineer - Offline Driving Intelligence
Leads ML initiatives to enhance validation processes using large-scale fleet and synthetic data for autonomous vehicle safety. Requires PhD or 5+ years ML experience, Python/PyTorch expertise, and AV domain knowledge.
Responsibilities
- Lead technical initiatives applying modern machine learning and large-scale data to critical validation problems at the intersection of ML and data science. Serve as key contributor and tech lead on a small team.
- Improve feature representation by extending and refining features and embedding space to identify and cluster interesting driving scenarios using first-principles thinking.
- Integrate AV performance data and metrics into models for more accurate risk predictions.
- Collaborate cross-functionally with system safety, data science, software, and fleet operations teams.
Qualifications
- PhD in a relevant field and/or 5+ years of experience with machine learning models and data science in industry.
- Expertise in machine learning concepts, including training deep learning models, evaluation, and optimization.
- Strong programming skills in Python and experience with PyTorch, TensorFlow, Jax.
- Experience with large-scale data processing and distributed computing.
- Domain knowledge in robotics, autonomous vehicles, perception, prediction, and planning.
- Proven ability to drive progress independently, lead technical projects, and apply critical thinking.
- Excellent communication skills for cross-functional collaboration.
Bonus Qualifications
- Real-world impact via patents, presentations, blog posts, publications at top ML conferences (Neurips, ICML, CORL, ICLR).
- Familiarity with encoder-decoder or foundation models for prediction and planning.
- Experience with test scripting and data analysis languages like SQL.
- Familiarity with fleet data collection and validation challenges in autonomous vehicles.
- Background in Bayesian optimization, online learning, and adaptive search.
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