Job Description
This role involves developing and applying advanced machine learning techniques to improve autonomous driving systems, focusing on planning, prediction, and robustness to create safe and feasible vehicle trajectories in real-world environments.
Key Responsibilities
- Develop scalable machine learning-based planning and prediction systems for autonomous driving.
- Research generative sequence modeling and sequential decision-making techniques.
- Collaborate with autonomy teams to develop holistic solutions for autonomy challenges.
- Propose, prioritize, and develop practical solutions for real-world autonomous vehicle issues.
- Deploy machine learning models and solutions on real-world autonomous vehicles.
Requirements
- Possess a deep expertise and prior experience in some or many of the following areas: sequential decision making, Imitation Learning, Deep Reinforcement Learning, generative modeling, large models pretraining finetuning, machine learning for robotics.
- Hold an M.Sc. or Ph.D. degree, preferably focusing on Computer Science, Artificial Intelligence, Mathematics, or a closely related field.
- Have subject matter expertise and research experience in one or more of the following areas: sequential decision making, Imitation Learning, Deep Reinforcement Learning, generative modeling, large models pretraining finetuning, machine learning for robotics.
- Have strong problem solving and programming skills in Python.
- Have beneficial programming skills in C.
- Have demonstrated research publications in top conferences such as NeurIPS, ICLR, ICML, CVPR, RSS, CoRL, or ICRA.
Benefits & Perks
Compensation/salary range: $160,360 to $240,540 per year
Annual performance bonus
Equity
Competitive benefits package
Ready to Apply?
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