Jobs at Zoox

Own Talent Acquisition program management, capacity planning, reporting, vendor relationships, tooling, and conference operations. Partner with Recruiting, HRIS, Legal, and senior leaders to deliver scalable hiring programs, improve recruiting infrastructure, govern data quality, support interview enablement, and guide responsible AI adoption in recruiting.

Develop deep learning models using imitation and reinforcement learning to generate and evaluate autonomous vehicle trajectories. Build production machine learning pipelines, metrics, and error-analysis tools, leveraging large-scale infrastructure. Collaborate with Planning, Perception, Simulation, and Systems Engineering teams to improve autonomous driving behavior in complex urban environments.

Manages vehicle technicians and fleet maintenance operations to maximize vehicle uptime across Zoox fleets. Leads hiring, onboarding, training, performance management, budgeting, KPI tracking, process improvement, safety compliance, and cross-functional initiatives. Optimizes maintenance and repair workflows, supports engineering testing, forecasts team growth, and drives operational changes across vehicle workshops and infrastructure.

Develop and maintain embedded Linux operating systems for autonomous vehicle devices. Configure Yocto build systems and U-Boot bootloaders, develop device drivers and kernel components in C, C++, or Rust, optimize performance, support hardware bring-up and manufacturing, and collaborate across software, hardware, release, and operations teams.

Build and operate Zoox’s continuous deployment platform, including its paved path, reliability, safety controls, and adoption across application teams. Partner with SRE and engineering teams to migrate services, turn recurring deployment friction into platform capabilities, establish safe production release standards, and mentor engineers. The role requires expertise in platform or infrastructure engineering, Kubernetes, container deployments, continuous delivery systems, programming, and infrastructure as code.

Leads technical program management for prototype sensor and compute hardware through high-volume manufacturing. Coordinates engineering, software, vehicle, product, manufacturing, quality, supply chain, finance, and contract manufacturing teams. Oversees roadmaps, schedules, production readiness, capacity planning, ramp milestones, budgets, resources, risks, and issue resolution. Establishes program processes and decision forums, communicates status to stakeholders, and manages Technical Program Managers.

Optimize GPU performance for Zoox’s motion planner, including profiling GPU hotspots, adapting software to multiple GPU architectures, reducing ML model latency and memory usage, and developing or optimizing CUDA kernels. Serve as a CUDA and GPU performance subject matter expert while working with complex multiprocess robotic systems in a Linux and C++ environment.

Own the triage program for autonomous vehicle fleet and simulation events. Lead defect classification and routing, monitor triage metrics, manage intake and escalations, coordinate tooling and automation, and forecast quarterly capacity across internal and vendor teams. Partner with software, QA, safety, product, vehicle operations, and program management stakeholders to improve accuracy, throughput, automation, and issue resolution.

Optimize GPU-based motion-planning algorithms for latency, memory usage, and resource utilization. Analyze performance metrics, identify GPU hotspots, adapt the planner across GPU architectures, optimize machine-learning models, and support engineers as a CUDA and GPU-performance subject matter expert. The role involves C++ development in large codebases, Linux environments, and debugging and profiling complex multiprocess robotic systems.

Define and lead vehicle experience product areas across current and future autonomous vehicle platforms. Own product execution throughout the lifecycle, understand customer and market needs, prioritize features, and align product strategy with business goals. Serve as Product Owner across hardware, firmware, software, and operations teams, driving cross-functional decisions and scalable, customer-focused vehicle experiences.

Owns diagnostic deployment for current and future service vehicle fleets, from requirements through release. Improves fault isolation, diagnostic quality, and time-to-diagnose using fleet data; maintains traceability across requirements, implementation, testing, and field performance. Defines service actions, develops prognostic and predictive-maintenance features, establishes diagnostic metrics, and drives continuous improvement with systems, firmware, software, service engineering, and fleet operations teams.

Leads Zoox’s perception data organization and data flywheel, connecting fleet signals, data discovery, curation, annotation, model training, evaluation, and performance measurement. Manages a multidisciplinary team of data science, data engineering, and labeling professionals. Drives automated annotation, intelligent mining of rare and safety-critical scenarios, log selection and storage, and rigorous tradeoffs among data quality, cost, speed, and scale. Partners with machine learning, metrics, evaluation, and infrastructure teams to improve autonomous-driving models.

Develop mission-planning algorithms for autonomous vehicles, including graph search and behavioral-planning integration. Build, test, and improve software directly on robotic platforms while collaborating across Mission Planning, Cloud Services, and vehicle autonomy teams. Contribute to technical direction, coordinate cross-functional initiatives, and create scalable solutions for sequential decision-making under uncertainty using MDPs and related frameworks.

Leads triage, containment, root-cause analysis, and permanent corrective actions for electrical-system issues identified during autonomous vehicle assembly and end-of-line testing. Partners with engineering, manufacturing, quality, suppliers, and operations to improve build readiness, manufacturability, production efficiency, and fleet reliability. Supports prototype builds, production trials, engineering changes, issue tracking, dashboards, and cross-functional resolution execution.

Lead policy, safety, and reputation communications for Zoox as it scales autonomous robotaxis toward commercial service. Develop proactive campaigns, manage media and reactive issues, translate regulatory developments into communications strategies, and advise senior stakeholders on sensitive matters. Partner with policy, safety, legal, product, and public affairs teams to build trust with regulators, communities, media, and the public.

Analyzes and diagnoses autonomous vehicle system faults across perception, planning, and AI software using on-road and simulation data. The role triages and prioritizes safety issues, performs root-cause analysis, identifies failure trends, develops tooling and workflows, and produces reports that guide engineering and leadership decisions on vehicle quality, safety, and robustness.

Own and scale Zoox’s continuous integration platform, improving build performance, reliability, cost efficiency, failure analysis, and developer support. The role involves operating distributed CI at scale, optimizing monorepo integration, applying AI tools to incident response, enabling engineering teams, establishing technical standards, and mentoring engineers.

Owns hardware-level functional safety and system-level sensor safety for cameras, LiDAR, and radar. Responsibilities include reviewing supplier documentation for SEooC and AoU alignment, validating ASIL compliance, executing board-level FMEDA for FPGAs and microcontrollers, defining diagnostic monitoring requirements, and supporting SOTIF simulation and physical testing for perception edge cases. Requires an engineering degree, at least three years of hardware experience, and knowledge of ISO 26262 and SOTIF.

Lead the Middleware Transport team responsible for in-vehicle messaging, networking, serialization abstractions, and vehicle-to-cloud connectivity. Own the roadmap, staffing, architecture, and release commitments while developing engineers and managing performance and hiring. Partner cross-functionally with firmware, security, simulation, manufacturing, fleet operations, and infrastructure teams. Balance reliability incidents with long-term platform architecture and establish technical standards for transport systems.

Lead end-to-end development and deployment of enterprise generative AI and LLM applications, including agentic workflows, MCP-based data integrations, secure tool usage, AI gateways, identity propagation, access controls, and observability. The role partners with Information Security and corporate functions to deliver governed AI automation across procurement, supply chain, legal, finance, HR, and manufacturing.