Staff Machine Learning Engineer, Waymo

• 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)

Desirable

• 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
• 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