zoox
Software Engineer, Fleet Simulation (Core Data Science)
At a Glance
- Location
- Foster City, California, United States
- Work Regime
- onsite
- Employment
- Full-time
- Compensation
- USD 191000-266000 per-year-salary
- Department
- Data Science
- Posted
- 2026-07-24T22:20:20.891000+00:00
Key Requirements
Required Skills
Benefits & Perks
ights, Amazon RSUs, health insurance, long-term care insurance, long-term an
Requirements
Software development experience in a production environment, with fluency in Python; or demonstrated experience learning new programming languages.
Experience building tools, services, or frameworks that make complex systems usable by non-specialist users.
Familiarity with any version control system, with preference for Git.
Experience designing metrics and building mechanisms that deliver robust, actionable insights.
Compensation & Benefits
Base Salary Range
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.
Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
Responsibilities
Turn existing fleet-simulation components into a coherent, self-service environment that data scientists and ML engineers can run without deep software expertise.
Fill gaps and build the connective tissue between simulation, data, and fleet-orchestration algorithms.
Build generalizable mechanisms that let teams measure how their orchestration algorithms affect fleet efficiency.
Collaborate with data science, ML, and fleet-orchestration teams to shape and prioritize the simulation roadmap.
Establish best practices and processes around simulation, evaluation, and data-driven decision-making.