Software Engineer, Fleet Simulation (Core Data Science) Software

Front Door Defense; Foster City (CA); On-site; USD 191,000 - 266,000; Full time

Benefits offered by this job

Health insurance

Zoox Stock Appreciation Rights

Amazon RSUs

Paid time off

Long-term care insurance

Long-term and short-term disability

Life insurance

Sign-on bonus

Job summary

Zoox in Foster City, CA is seeking a Software Engineer, Fleet Simulation (Core Data Science) to build a self-service fleet simulation environment for data scientists and ML engineers. You will turn existing components into a coherent platform, connecting simulation with data and fleet orchestration, enabling measurement of how algorithms affect fleet efficiency.

The role requires strong Python development, experience building usable tools, and collaboration with cross-functional teams.

Qualifications

• Fluency in Python in a production environment or demonstrated ability to learn new languages.
• Experience building tools, services, or frameworks that make complex systems usable by non-specialist users.
• Familiarity with version control systems (Git preferred).
• Experience designing metrics and building mechanisms that deliver robust, actionable insights.
• Good communication and collaboration skills.

Responsibilities

• Turn fleet-simulation components into a coherent, self-service environment for data scientists and ML engineers.
• Fill gaps and build connective tissue between simulation, data, and fleet-orchestration algorithms.
• Build generalizable mechanisms to measure how 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.

Skills

Python

C++

Kotlin

Algorithm design

Metrics design

Systems thinking

Communication

Tools

Git

Job description

Software Engineer, Fleet Simulation (Core Data Science)

Build a self-service fleet simulation environment for data scientists and ML engineers

Location: Foster City, California

Compensation: $191,000 - 266,000 USD / year

About The Role

Core Data Science Team Role

The 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).

$191,000 - $266,000 a year 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,

• 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
• life insurance

Zoox 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.

If you need an accommodation to participate in the application or interview process please reach out to [e-mail] or your assigned recruiter.

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.