The Planner Reasoning Team builds technology that has an extremely broad impact across the Waymo organization and is the team most directly responsible for the Waymo Driver’s behavior. We have wide reaching impact into both onboard and off-board system architecture, paving the way for future-looking deep-learning-based explorations. The Data-Driven Reasoning team within Planner Reasoning enables new data-driven approaches of Reasoning to improve the Waymo Driver.  In this team, your work will include auto-labeling training data, adding Reasoning logic into ML models, data-driven evaluation, data introspection/understanding, and more! 

In this hybrid role, you will report to a Technical Lead Manager.

You will:

• Design, develop, and implement ML solutions for autonomous vehicle planning including, but not limited to, modeling, reward/loss shaping, finetuning, reinforcement learning, data shaping, etc.
• Analyze model performance using data-driven techniques to evaluate and compare different approaches
• Stay up-to-date with the latest advancements in autonomous driving and machine learning, and be able quickly prototype, experiment and deploy novel SOTA solutions
• Collaborate closely with partner teams such as perception, research, simulation, and evaluation
  

You have:

• Experience in applied machine learning including deep learning models, reinforcement learning, feature engineering, loss/reward shaping, data shaping, fine tuning and model evaluation
• Proficiency in Python and at least one deep learning frameworks (e.g. PyTorch, JAX, or TensorFlow)
• Proficiency in dealing with large scale models and datasets
• Experience in integrating ML models into complicated systems
• PhD, Masters or Bachelors degree in Computer Science, Machine Learning, Robotics, or a related field
  

We prefer:

• Experience in the autonomous driving domain, including areas like motion planning or perception
• Experience with Large Language Models (LLM) or Vision Language Models (VLM), prompt engineering and chain of thought reasoning
• Experience in applying ML to a robotics problem
• Evaluation experience, contributing to scalable evaluation workflows and building metrics for ML models
• Proficiency in C++