Senior/Staff Software Engineer - Machine Learning & System Optimization

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 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 looking for an AWS Cloud Security Engineer to lead the design and implementation of secure, scalable, and software-defined infrastructure in our AWS cloud environment. This role is responsible for establishing best-in-class security practices across AWS, driving automation-first infrastructure security, and partnering with engineering and platform teams to embed security into every layer of our technology stack. You’ll act as a security champion, ensuring that infrastructure designs meet the highest standards of confidentiality, integrity, and availability — while maintaining operational efficiency and scalability through Infrastructure as Code (IaC). In this role, you will: Define and own the multi-year security architecture and roadmap for Zoox's robots and fleet, spanning embedded/firmware, in-vehicle networks, cloud, and supporting infrastructure. Partner with hardware, firmware, autonomy, and infrastructure engineering teams to embed security requirements into system design from the ground up, rather than bolting them on after the fact. Lead threat modeling and architecture reviews for new vehicle platforms and major feature launches, identifying and prioritizing systemic risk across the fleet. Set technical standards and guardrails - secure boot, key management, network segmentation, update/OTA security, and more - and drive their adoption across engineering teams. Represent Product Security in cross-functional and leadership discussions, translating technical risk into business and safety impact for the organization. Qualifications 10+ years of experience in security engineering, including significant time in an architect, staff, or technical lead capacity. Deep expertise in embedded/IoT security, including secure boot, TPM/TEE, cryptographic key management, and hardened firmware/OS design. Demonstrated experience architecting security for complex, physical/cyber-physical sys

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 Autonomy Behaviors team is responsible for producing our vehicle’s driving trajectory. As a Principal ML Engineer, you will lead the technical development of machine learning algorithms for our next-generation ML Planner. Your impact will range from delivering innovations for immediate milestones to pioneering exploratory projects. You will collaborate closely with teams specializing in Foundation Models, Perception, Simulation, and Safety Validation, in influencing our autonomy stack. Your role will look at problems in a way that crosses team boundaries to prototype new approaches that influence the long term technical direction of multiple organizations within the company. In this role, you will: Set the technical direction of ML development for the future of our Planner Push the frontiers of imitation learning, reinforcement learning, and model scaling to develop new ML models for our onboard Planner Identify and drive force-multipliers for ML development, including metrics, data, and training frameworks Develop new methods to leverage Zoox’s Foundation Models into the ML Planner Provide technical mentorship to the broader group of ML developers at Zoox Collaborate with engineers across Autonomy Software, Simulation, System Design and Mission Assurance, and other departments to solve the overall Autonomous Driving problem in complex urban environments Qualifications BS, MS, or PhD degree in computer science or related field Proven track record of technical leadership in large-scale AI organizations Significant experience with training and deploying Deep Learning models to production Fluency in C++ or Fluency in Python with a basic understanding of C++ Extensive experience with programming and algorithm design-Strong mathematics skills, 10+ years of experience Bonus Qualifications Conference or Journal publications in Machine Learning or Robotics related v