Staff Machine Learning Engineer, Vehicle Compliance Reasoning

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 are the software engineering team responsible for Waymo's high-level motion planning, encoding Waymo's desired driving behaviors onboard and offboard. Our mission is to build the driving logic needed to deliver a safe, excellent Waymo Driver at scale. We have wide reaching impact into both onboard and off-board system architecture, paving the way for future-looking deep-learning-based explorations. In this team, you'll have an impact on scaling our Waymo Driver's performance and maintaining and improving our excellent safety record as Waymo expands to more cities. 

In this hybrid-based role, you will report to an Engineering Manager.

You will: 

• Lead and develop ML solutions for the Waymo driver's decision making and motion planning -- shaping the data, reward, or loss functions in modeling, data mining from large datasets, developing and refining labeling policies.
• Analyze, finetune, and evaluate model performance using data-driven approaches
• Integrate and deploy ML models on the fleet, conduct end-to-end validation and on-field monitoring.
• 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
• Mentor engineers in leading adoption of ML-based approaches for solving reasoning problems.

You have: 

• PhD, Masters or Bachelors degree in Computer Science, Machine Learning, Robotics, or a related field
• 7+ years of years of software engineering / machine learning experience
• 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 dealing with large scale models and datasets
• High quality API design with an eye towards eval and data driven technique
• Experience with working and solving design problems that cut across multiple components
• Proficiency in Python and at least one deep learning frameworks (e.g. PyTorch, JAX, or TensorFlow)

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
• Eval experience, contributing to scalable eval workflows and building metrics for ML models
• Proficiency in C++