Software Engineer, Fleet Simulation (Core Data Science)
Job Description
Job DescriptionThe Core Data Science team builds the products and data assets that let teams across Zoox measure and improve the autonomy and operational performance of our fleet. In this role, you'll focus on fleet simulation — the environment our data teams use to develop, test, and evaluate the algorithms that orchestrate our autonomous fleet (dispatch, routing, and vehicle assignment) and to understand how those algorithms perform before they reach the road. You’ll piece together the constituent components into a coherent, easy-to-use simulation environment, filling in the gaps, and building generalizable mechanisms so data scientists can measure their algorithm's impact on fleet efficiency. You'll join a diverse, experienced team with rapidly growing scope while working with one of the industry's most valuable autonomous vehicle datasets.In this role, you will:
- 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.
Qualifications
- 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.
- Good communication and collaboration skills.
Bonus Qualifications
- Basic familiarity with C++ and/or Kotlin.
- Experience with microservices and/or distributed systems.
- Experience with simulation and/or fleet orchestration (dispatch, routing, vehicle assignment).
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.About ZooxZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
Follow us on LinkedIn
AccommodationsIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.
A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.