Senior Software Engineer, Statistical Evaluation and Sampling
About The Position
Waymo is an autonomous driving technology company focused on building the Waymo Driver to improve access to mobility and save lives. The Waymo Driver powers Waymo's fully autonomous ride-hail service and can be applied to various vehicle platforms and product use cases, having provided over ten million rider-only trips and autonomously driven over 100 million miles on public roads and tens of billions in simulation. Waymo's Release Evaluation organization ensures the safety of each Waymo Driver version before deployment by building automated pipelines to identify rare and exceptional scenarios under time and resource constraints. The Sampling and Efficiency team within Release Evaluation specifically applies importance sampling techniques and machine learning to maximize the statistical efficiency of these discovery pipelines.
Requirements
- BS in Computer Science, Robotics, Statistics, Physics, Math or another quantitative area
- Fluency with probability and statistics
- Strong self-motivation to navigate complex systems and pursue open-ended problems to completion
- 5+ years of experience with Navigating and modifying a large code base containing a variety of languages, such as C++, Python and SQL
- 5+ years of experience with Performing statistical analyses
- 5+ years of experience with Building data processing pipelines
- 5+ years of experience with Writing, reviewing, and merging code following industry standards for code health and maintainability
Nice To Haves
- 7+ years of industry experience (or 3+ years post-doc experience) in a quantitative engineering role, including a proven track record as a technical lead navigating complex, multi-language codebases (C++, Python, SQL) to drive the end-to-end experimental lifecycle: developing hypotheses, designing and executing large-scale experiments, and building robust data pipelines
- Experience programming in C++
- Experience developing and evaluating sampling methods
- Experience designing, training, evaluating, and applying ML models
- Experience working in the AV industry
- PhD in a quantitative field
Responsibilities
- Develop importance sampling techniques that enable our evaluation pipelines to deliver better signals with fewer resources
- Find signals in our logs and simulations that might help us to more efficiently discover rare and important events
- Build systems that systematically optimize multiple objectives under resource constraints
- Collaborate with other engineers, data scientists, statisticians and the leadership team to deliver evaluation products and help make data driven decisions
- Champion code health and best practices in a large and complex code base
Benefits
- discretionary annual bonus program
- equity incentive plan
- generous Company benefits program
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
