Senior Machine Learning Engineer, Prediction & Planning, System Architecture
Role details
Job location
Tech stack
Job description
The system architecture team handles the onboard contract of the model with the system, including kinematics, interfaces and representations.Our team's mission is to work across the stack, building the best setup for the model to drive. We tackle this through projects in data, modeling, metrics, and the overall planner system.
In this hybrid role, you will report to a Technical Lead Manager.
You will:
- Tackle challenging real-world problems with ML and engineering solutions.
- Use state of the art techniques to design and build ML models, deploy them in the real world on production vehicles
- Design and build the necessary architectures, algorithms, pipelines and evaluation systems on Google's extensive data infrastructure
- Collaborate with researchers, product area owners and engineers to develop safe, smooth planning behavior for all road users & deliver product requirements.
Requirements
- Bachelors in Computer Science, ML, Robotics, similar technical field of study, or equivalent practical experience
- Hands-on experience with modern deep learning libraries (eg: TensorFlow, JAX, Pytorch)
- Proficient programming skills (eg: Python, C/C++)
- Strong analytical and problem solving skills
- 4+ years of experience in Machine Learning modeling and/or Autonomous Vehicles systems
We prefer:
- MS or PhD in Computer Science, Machine Learning, Robotics, or a related field
- Publications in top-tier conferences such as ICML, NeurIPS, CVPR, ICCV, ECCV, ICLR, IROS, CoRL, ACL, or EMNLP
- Prior software development or ML research industry experience (including internships)
- General software engineering experience solving motion planning or related robotics problems
- Experience applying or evaluating ML-based systems in production environments
- Experience with performance optimization of deep models, including with respect to specific hardware architectures
Benefits & conditions
The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo's discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements. Salary Range