Senior Software Engineer, Eval Efficiency & Optimization
About this role
The day-to-day work for this Senior Software Engineer involves tackling complex, ill-defined problems situated at the intersection of statistics, machine learning, and scalable systems engineering. The engineer will focus on developing creative quantitative models to resolve evaluation challenges and providing rigorous mathematical and experimental validation for the statistical efficiency of their solutions. A key responsibility is designing and building automation to improve the efficiency and scalability of the evaluation infrastructure. This role exists to enhance Waymo's evaluation pipelines, ensuring they deliver better signals with fewer computational resources. Collaboration is essential, working alongside data scientists, product managers, and leadership to translate these technical evaluations into data-driven decisions.
This position is ideal for a candidate who thrives on ambiguity and can reduce complex systems into manageable quantitative models. The successful candidate will champion code health and best practices within a large and intricate codebase. It requires a strong ability to adapt techniques from research papers into practical, applied solutions within a high-stakes autonomous driving context. Individuals who are self-motivated and comfortable pursuing open-ended problems to completion will find this environment suitable.
What you will do
- Develop creative quantitative models to address evaluation challenges.
- Provide rigorous mathematical and experimental proof for the correctness and statistical efficiency of solutions.
- Tackle ill-defined and ambiguous problems by reducing complex systems into tractable quantitative models.
- Design and build automation to enhance the efficiency and scalability of the evaluation infrastructure.
- Collaborate with engineers, data scientists, product managers, and leadership to deliver evaluation products.
- Champion code health and best practices within a large and complex codebase.
What you need
- A Bachelor of Science degree in Math, Physics, or another quantitative field is required.
- Fluency in implementing statistical, ML, and general mathematical algorithms for large datasets is necessary.
- Experience adapting techniques from research papers to applied problems is important.
- Possesses 3 to 5 years of experience navigating and modifying a large codebase containing languages like C++, Python, and SQL.
- Ability to perform statistical analyses effectively.
- Proficiency in writing, reviewing, and merging code following industry standards for code health and maintainability.
Nice to have
- PhD in a quantitative field
- Experience programming in C++ and Python
- Experience developing, evaluating, and deploying products at scale
- Experience with Agentic AI
Benefits
- Discretionary annual bonus program
- Equity incentive plan
- Generous Company benefits program
Skills and tech stack
Questions candidates ask
What is the remote policy for this role?
The job is listed with locations in Mountain View, CA, USA; San Francisco, CA, USA; and New York, NY, USA.
What is the compensation range for this position?
The expected base salary range for this full-time position across US locations is listed as $213,000 — $263,000 USD.
What is the required technical background?
Candidates need fluency in implementing statistical, ML, and general mathematical algorithms for large datasets, along with experience in C++ and Python.
What opportunities are there for professional development?
Employees are eligible to participate in Waymo’s discretionary annual bonus program and equity incentive plan.