Senior/Staff Software Engineer - Ride and Fleet Services

On the Motion Planning team at Zoox, you’ll be dedicated to improving the driving behaviors of the robot on public roads. The Planner's job is to figure out where the robot is going and how to get there safely in situations as complex as those found in Downtown San Francisco or on the Las Vegas Strip. This is a cutting-edge problem, which requires teamwork and collaboration across a broad set of experts spanning Planner, Perception, Prediction, Operations, and more. Together, you will create the next generation of algorithmic improvements to expand our robot’s ability to drive in some of the most complex situations found on public roads. Safety is foundational at Zoox, so you will take a measured approach – develop a principled modification to the Planner, test in simulation and on closed courses, and team up with our safety drivers for on-road testing. In this role, you will: Create principled algorithmic improvements to specific areas of driving behavior and implement those changes in our code base. Use our extensive backend tooling to test your changes across many different driving situations at the press of a button. Lead on-vehicle drive reviews to generate actionable feedback on driving performance. Use this experience to help the team learn and make improvements. Attend conferences and survey literature to stay informed on the most recent developments in the fields of Robotics and Motion Planning. Write and file patents for novel technologies you develop. Qualifications Master's degree in Computer Science or a related field and 8+ years of experience Fluency in C++ Understanding of configuration spaces and a variety of planning techniques (A*, RRTs, PRMs, etc.) Demonstrated ability to create real-time motion planning algorithms Bonus Qualifications Significant contributions to geometric- and/or sampling-based planning algorithms Experience with autonomou

Zoox is building fully autonomous vehicles designed from the ground up for robotaxi service — and as we scale toward launch, our engineering infrastructure has to scale with us. We're hiring a Staff Site Reliability Engineer to own source control at Zoox, serving as the technical lead for the platform that every engineer depends on daily. This is a hands-on lead role. You'll set the direction for our Git-based monorepo, drive a restructuring of our Source Code management strategy, build the tooling that improves reliability and developer workflows, and partner with platform, security, and product teams to make source control a strategic asset rather than a bottleneck. The ideal candidate leads by building — with deep expertise in monorepo management (branching strategies, code review workflows, access controls, CI/CD) and a track record of improving developer productivity through code, not just guidance. You take ownership, measure what matters, and have the technical credibility to make decisions stick. In this role, you will: Own the technical strategy and roadmap for source control at Zoox. Plan and execute a strategic effort to scale source code management at Zoox: scoping, design, implementation, cutover, and validation, in partnership with security, platform, and engineering teams. Build and operate monorepo scalability improvements across repo structure, branch strategy, code ownership, large-file handling, and CI integration — including the scripts, hooks, and automation that make them stick. Develop the guardrails and developer-facing tooling that reduce toil for SRE and product engineering alike, measured by build times, merge friction, and interrupt volume. Set the technical bar through code reviews, design proposals, and pairing — and serve as the hands-on authority for source control decisions across Zoox engineering Qualifications 5+ years operating GitH

Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in large-scale Foundation models, VLMs, and VLAs to make autonomous driving as seamless as possible. The Opportunity Are you excited to drive our ML Performance Optimization initiatives and make our ML models that enable autonomous driving as fast and efficient as possible? You will get to work with SOTA accelerators, cutting-edge techniques in distributed training, quantization, distillation, and pruning, among other things, working closely with all the Autonomy teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. We build and operate the base layer of ML tools, model development, and serving systems that our applied research teams use for in- and off-vehicle ML use cases. You will work alongside a team of strong software engineers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here. If you want to learn more about our ML Infrastructure, here is one of our past talks at re:Invent. In this role, you will: Lead the design, implementation, and operation of training performance optimizations (data/tensor/pipeline parallelism, mixed precision, gradient checkpointing, GPU kern

The Behavior Capabilities opportunity falls within the Fail Operational Planning team at Zoox. This team works to ensure that the robot continues to operate effectively, even in the presence of minor compartmentalized failures or degraded capabilities. The focus of the team includes developing behavioral and motion planning algorithms to improve trip progress, vehicle uptime metrics, and correspondingly a better customer experience. This is a cutting-edge problem which requires teamwork and collaboration across a diverse group of experts including Planner, Perception, Prediction, Hardware, and more. On this team, you will contribute to the next generation of algorithmic advancements to expand our robot’s ability to drive in some of the most complex scenarios. We are looking for an engineer who is excited to understand the interdependencies within the driving stack and takes ownership of their projects and has a holistic product focused approach towards development. In this role, you will: Create principled algorithmic improvements to specific areas of driving behavior and implement those changes in our code base. Collaborate cross-functionally to develop strategies and intelligent behaviors to mitigate the performance degradation under various failure modes of the system. Architect and implement scalable solutions ensuring seamless integration with the rest of the driving stack. Partner with validation teams to define and execute tests for developed algorithms. Qualifications: Master's degree in Computer Science or related field and 9+ years of experience Fluency in C++ Extensive experience with programming and algorithm design Understanding of vehicle kinematics Bonus Qualifications PhD in Computer Science, Electrical Engineering, Mechanical Engineering, or related field Experience shipping products to market (commercial robotics, drones, consumer devices etc.) Demon

Zoox is on a mission to reimagine transportation and ground-up build autonomous robotaxis that are safe, reliable, clean, and enjoyable for everyone. We are still in the early stages of deploying our robotaxis on public roads, and it is a great time to join Zoox and have a significant impact in executing this mission. The ML Platform team at Zoox plays a crucial role in enabling innovations in large-scale Foundation models, VLMs, and VLAs to make autonomous driving as seamless as possible. The Opportunity Are you excited to drive our ML Performance Optimization initiatives and make our ML models that enable autonomous driving as fast and efficient as possible? You will get to work with SOTA accelerators, cutting-edge techniques in distributed training, quantization, distillation, and pruning, among other things, working closely with all the Autonomy teams within Zoox - Perception, Prediction, Planner, Simulation, Collision Avoidance, and have the opportunity to significantly push the boundaries of how ML is practiced within Zoox. We build and operate the base layer of ML tools, model development, and serving systems that our applied research teams use for in- and off-vehicle ML use cases. You will work alongside a team of strong software engineers and act as a force multiplier for our internal customers. This team has many growth opportunities as we expand our robotaxi deployments and venture into new ML domains. If you want to learn more about our stack behind autonomous driving, please look here. If you want to learn more about our ML Infrastructure, here is one of our past talks at re:Invent. In this role, you will: Develop and execute a strategic vision for the ML Performance Optimization team to unlock ML innovation in autonomous driving and rider experience. Lead the design, implementation, and operation of cutting-edge ML Training OR Inference performance optimization techniques to scale our VLM, VLA, and Foundational models and deplo

Zoox's Robot Software Infrastructure team is seeking a passionate software engineer to help develop and advance the common performant operating system that powers several devices on our vehicle including Autonomy systems. This team develops platform-level software and services, including operating systems that enable complex, hardware-accelerated workloads critical for autonomous driving on automotive-grade hardware. We work closely with cross-functional teams—including developers, release management, hardware engineering, manufacturing and operations—to support vehicle development and deployment at scale. You'll have the opportunity to influence the next generation of our platform, hardware, and robotaxi. If you are excited to explore a broad problem space and are mindful of how components fit within a larger system, you may be a great fit! In this role, you will: Design, develop, and maintain the operating system platform that powers various on-bot devices and applications Architect and implement platform-level software to support robust and scalable robotics infrastructure Configure and manage embedded Linux build systems (e.g., Yocto) and bootloader processes (e.g., U-Boot) to ensure reliable system startup and maintenance Develop and optimize device drivers and kernel-space components using C, C++, or Rust to meet performance and reliability requirements Collaborate cross-functionally to support seamless integration and delivery of the OS platform, triage issues, support new hardware bring-up and manufacturing functions Qualifications 8+ years delivering production systems and software applications, 2+ years of delivering custom Embedded Linux operating systems Have a deep understanding of Linux, build systems like Yocto, and bootloaders like U