Senior Software Engineer, Vehicle Deployment

Zoox's Robot Software Infrastructure team is seeking a passionate software engineer to help develop Robot software and infrastructure to 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 application software engineering, release management, hardware engineering, manufacturing and operations—to support vehicle development and deployment at scale. If you are excited to explore a wide 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 end-to-end continuous integration and validation toolchains for the operating system platform that powers various on-bot devices and applications on the Robotaxi Architect and implement platform-level software to support robust and scalable robot software 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 Designed and deployed end-to-end continuous integration and validation toolchains to verify Linux/OS images for production software releases supporting different hardware platforms Proficiency in Linux internals, including init systems, containerization,

Zoox is developing state-of-the-art autonomous vehicle software for our purpose-built vehicle. We believe that developing the end-to-end product will not only help us scale our services but will also result in a superior customer experience. In this role, you will build and operate the continuous deployment platform that carries changes from merge to production. You will own both the platform and its adoption: building the paved path that every production change travels on and working directly with application teams to move them onto it. We are looking for an engineer who is opinionated about what the right path looks like, who has the judgment to decide where to hold the line and where to leave room for the team, and who has a strong bias toward execution. This is a critical role to remove friction from our release process, improve the deployment experience for everyone in the software organization, and ultimately help us scale our autonomous vehicle fleet to more riders and more cities. In this role, you will: Own the reliability and operational excellence of our deployment platform Build and own the paved path for continuous delivery, and own the safety net that makes the platform trustworthy Work cross-functionally with application teams and SRE to move services onto the paved path, turning recurring friction into platform capability rather than one-off support Set the technical bar for how code is shipped safely to production, and mentor the engineers around you Qualifications 5+ years of software engineering experience, including significant experience in platform, infrastructure, or production operations Hands-on experience with a continuous deployment system in a large organization, Harness preferred; ArgoCD, Spinnaker or other relevant systems Hands-on experience with Kubernetes and container-based deployments Expertise wit

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

The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence. As a Machine Learning and System Optimization Engineer, you will orchestrate and allocate overall system capacity to various core perception models running on-bot, as well as drive large initiatives that allow for more efficient inference by sharing various parts of the perception stack with one another. You will focus on bringing highly efficient, production-ready large-scale models to our on-vehicle stack. We are looking for experts with hands-on experience compressing, accelerating, and deploying complex models, including LLMs, VLMs, or foundation models, for power- and thermal-constrained vehicle SoCs. In addition, you will optimize ML models, write custom CUDA kernels, and build highly concurrent inference code to ensure real-time, deterministic execution on edge devices. In this role, you will: Allocate and distribute system resources (CPU/GPU/interconnect) to various models and inference engines running on the robot. Spearhead cross-cutting initiatives that allow for better compute utilization through sharing/fusing models and better scheduling strategies. Optimize large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs) using advanced quantization (PTQ, QAT), pruning, mixed-precision inference frameworks, and parameter-efficient fine-tuning (LoRA, QLoRA). Architect and implement model conversion and compilation pipelines using TensorRT for edge deployment. Write production-level, low-latency, and memory-safe C++ and CUDA code for real-time inference on vehicle systems. Qualifications: Deep experience in system and performance optimization in CPU/GPU systems designed for low latency or high throughput. Deep expertise in working with real-time systems & required

Zoox is on an ambitious journey to develop a full-stack autonomous mobility solution for cities and safely deploy such a robotaxi solution. The System Design and Mission Assurance (SDMA) team plays a foundational role in the company's success, responsible for constructing the safety case and fail-operational design for our autonomous driving robots before public road deployment. We are seeking a highly motivated V&V software development engineer in test (SDET) to join this systems-engineering department. As a V&V SDET, you will be a technical lead, owning the end-to-end validation strategy for critical safety systems while architecting and implementing the advanced software infrastructure required to verify them. This role is coding-intensive, focused on building solutions for high-fidelity testing, scalable automation frameworks, and sophisticated data analysis tools to ensure successful compliance to requirements and mission success. Some examples of tools this role supports: Framework for event definition, orchestration, and verification High-performance C++ and Python-based emulators for vehicle sensors (e.g., Radar, Lidar, and Inertial Measurement Units) to enable realistic, real-time fault injection Robust communication bridges between simulation environments and physical vehicle hardware Automating test management and reporting within lifecycle management tools, e.g. Polarion, JAMA, DOORS. In this role, you will: Lead the design and maintenance of large-scale event-driven software/hardware -in-the-loop (SIL/HIL) testing frameworks, utilizing advanced software patterns to improve modularity and reduce code duplication. Architect and manage end-to-end continuous integration (CI) pipelines to automate the execution of regression suites. Lead root cause analysis for complex system-level failures, developing log mining scripts and visualization dashboards (e.g., Grafana, SQL-based notebooks) to triage failures and track performance metr

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