Jobs at Zoox

Research, implement, and optimize machine learning methods for high-fidelity 3D simulation and autonomous vehicle development. Responsibilities include training generative and world models, building scalable cloud pipelines, improving rendering and data-generation tooling, and integrating ML techniques into production simulation systems. The role collaborates with researchers, technical artists, and simulation engineers and focuses on 3D vision, reconstruction, radiance fields, and rare-scenario generation.

Develops and optimizes machine learning models for realistic 3D simulation, including 4D generative and world models for rare autonomous-driving scenarios. Responsibilities include researching 3D vision methods, building scalable cloud pipelines, integrating ML techniques into production simulation, and improving rendering and data-generation tools. The role requires experience with Python or C++, radiance fields, 3D or video generative models, 3D reconstruction, human-centric vision, and probabilistic techniques.

Develop exterior designs for Zoox robotaxi platforms and connected hardware from concept through production and deployment. Create sketches, renderings, CAD, models, and presentations while maintaining design intent, craftsmanship, and quality. Collaborate with engineering, software, product, brand, and manufacturing teams to balance creative ambition with technical feasibility and manufacturing constraints.

Design and build low-latency C++ connectivity infrastructure for autonomous vehicles, including shared-memory IPC, inter-host transport, pub/sub and RPC APIs, serialization, and time synchronization. Improve reliability during process and host failures, reduce latency and jitter, evolve schemas, troubleshoot fleet and simulation issues, and lead technical designs spanning multiple teams.

Develop and deploy AI-powered decision tools and agentic workflows for safety operations. Build LLM integrations with safety databases and operational logs, evaluate model reliability and failure modes, create APIs or dashboards, and collaborate with safety strategists and software engineers to validate prototypes in real-world autonomous vehicle scenarios.

Analyze autonomous vehicle, fleet, and business data to develop metrics, evaluate model and simulation performance, identify behavioral patterns, and support data-driven decisions. Projects may include drift monitoring, automated retraining, predictive modeling, similarity search, and statistical testing. The intern will use Python and SQL, apply machine learning and analytical methods, collaborate with simulation and autonomy teams, and communicate findings to varied audiences.

Analyze autonomous vehicle fleet safety data, incident logs, telemetry, simulation results, and operational metrics. Support benchmarking against industry and regulatory standards, build automated data pipelines and dashboards, validate data integrity, and communicate insights to safety, engineering, systems integration, and fleet operations teams. The internship requires a full-time 12-week commitment and relocation to the Bay Area.

Supports Zoox’s autonomous fleet infrastructure operations by improving vehicle parking capacity, assessing depot readiness across vehicle platforms, developing adverse-weather return-to-base plans, and evaluating future charging, inspection, and site infrastructure needs. The intern will coordinate with operations, facilities, engineering, security, legal, and external partners while building analyses, models, dashboards, and infrastructure roadmaps.

Own technical programs that scale simulation, cloud infrastructure, automation, AI-assisted triage, metrics, and release evaluation for autonomous vehicle software. Partner cross-functionally to convert research and prototypes into production systems, reduce development and validation cycle times, expand virtual testing, and improve release cadence. Measure bottlenecks and communicate data-backed progress to executive leadership.

Software Engineering Interns design, implement, test, document, and present software for Zoox’s autonomous vehicle systems. Projects may involve profiling tools, network schedulers, automated checkers, middleware, security, simulation, or sensor tooling. Interns evaluate designs through experiments, benchmarks, and research while collaborating with engineering teams. The internship is full-time for 12 weeks in the Bay Area and provides exposure to software foundations supporting autonomy and robotics.

Hardware Engineering Interns support autonomous vehicle systems through electrical and functional validation, failure root-cause analysis, hardware stability tooling, quality and reliability analysis, supplier assessments, and sourcing projects. They analyze engineering and supplier data, recommend improvements, and present findings to cross-functional stakeholders. The role requires Python or similar data-analysis tools, hands-on lab equipment experience, strong analytical skills, and relocation to the Bay Area for a full-time summer internship.

Hardware Engineering Intern supporting Zoox Manufacturing Operations through production hardware development, test automation, diagnostics, process optimization, logistics, prototyping, and manufacturing data analysis. Responsibilities may include improving assembly and logistics processes, developing work instructions and automation tools, analyzing production data, and presenting recommendations to engineering and manufacturing stakeholders. The internship is full-time for 12 weeks in the Bay Area beginning May or June 2027.

Software engineering interns build services, tools, applications, firmware, testing automation, and embedded software supporting Zoox’s autonomous fleet. Projects may involve vehicle-cloud platforms, firmware, software integration, QA, site reliability, or rider-facing software. Interns improve reliability, performance, observability, and diagnostics while collaborating with software, firmware, and hardware engineers. The role is a full-time, 12-week internship in the Bay Area beginning May or June 2027.

Software Engineering Interns will develop and evaluate algorithms and machine learning models for Zoox’s autonomous driving system. Responsibilities include training models on large-scale driving and simulation data, analyzing failure modes, writing production-quality C++ and Python, participating in code reviews, communicating technical results, and potentially contributing to publishable research across autonomy behaviors, perception, routing, or collision avoidance teams.

Interns prototype and build AI-enabled tools, automations, integrations, data pipelines, dashboards, and enterprise-system solutions for business needs. They collaborate with technical and business teams, translate requirements into scalable solutions, document work, and present results. Potential focus areas include business applications, enterprise data and AI, information security, IT infrastructure, and HRIS.

Hardware engineering interns design, model, simulate, test, and validate vehicle components or subsystems for Zoox’s autonomous robotaxi. Responsibilities include using CAD and simulation tools, analyzing test data, investigating build or testing issues, proposing design fixes, documenting work, and presenting results. Interns may work on vehicle integration, packaging, powertrain, thermal and electrical systems, chassis, body, industrial design, or the robot platform.

Owns the full lifecycle of PMO processes and tools, including requirements, documentation, configuration, integrations, training, rollout, support, and retirement. Partners with IT, engineering, and operations stakeholders; manages plans, milestones, risks, reporting, and communications. Uses Jira, Confluence, AI tools, automations, dashboards, and applications to improve program execution and decision-making.

Own marketing and customer promotions forecasting, budgeting, accruals, variance analysis, ROI modeling, and performance reporting. Partner with Marketing, Commercial, Product, Data Science, and Accounting to evaluate campaigns, rider incentives, pricing experiments, and market launches. Build financial models and dashboards using large datasets to connect rider funnel performance with gross bookings, contribution margin, profitability, and P&L impact.

Lead the technical vision and strategy for GPU execution across Zoox’s onboard AI platform. Own how perception, prediction, and planning workloads are scheduled, shared, isolated, and optimized across vehicle GPUs under fixed power, thermal, cost, safety, and real-time constraints. Partner with ML, autonomy, middleware, hardware, and infrastructure teams to improve onboard compute efficiency across future vehicle generations.

Lead the architecture, development, and deployment of Collision Avoidance System perception algorithms for autonomous vehicles. Design safety-critical C++ systems combining lidar, radar, camera, classical geometry, tracking, sensor fusion, and machine learning under strict latency and compute constraints. Own the technical roadmap, collaborate across autonomy and safety teams, define evaluation metrics, and mentor engineers while ensuring reliable production deployment.