Waymo is looking to improve the performance and safety of its autonomous driving technology by addressing issues in reinforcement learning, such as the sim2real gap, reward formulation, model interpretability, and safety verification. The goal is to impact future Waymo driving behavior and improve rider-only trip experiences.
Requirements
- Experience with deep learning concepts and reinforcement learning
- Proficient in Python and deep learning frameworks such as PyTorch, JAX, or TensorFlow
- Experience in the autonomous driving domain, including areas like motion planning, perception, or control
- Experience in integrating ML models into complicated systems
- Proficient in C++
- Conferences such as CVPR, ICCV, ECCV, ICLR, ICML, NeurIPS, IROS, CoRL
Responsibilities
- Collaborate with researchers and engineers to design, development and implement deep reinforcement learning models for autonomous vehicles planning
- Analyze model performance, triage failure cases, and identify opportunities for improvement.
- Tune the model as needed to improve performance
- Stay up- to - date on the latest advancements in autonomous driving and machine learning
Other
- Currently pursuing a Masters/PhD degrees in Computer Science, Machine Learning, Robotics, or a related field
- This will be a hybrid onsite internship position.
- We will accept resumes on a rolling basis until the role is filled.
- To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in.
