Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

Designs and develops automotive body structures, including body-in-white, crash structures, underbody systems, and vehicle integration. Leads component development from concept through production, defining requirements, schedules, validation plans, and quality processes. Collaborates with styling, packaging, CAE, testing, manufacturing, suppliers, and management while supporting material and manufacturing decisions. Requires automotive body engineering experience, mechanical engineering education, CATIA proficiency, and knowledge of DFMEA, DVP, PVP, APQP, DFSS, and GD&T.

Own the electrical and electrical-distribution program scope for autonomous vehicle programs involving external engineering partners. Coordinate EE work packages, manage RASIC ownership, change control, data exchange, PLM and drawing releases, supplier readiness, milestone planning, risk recovery, and executive reporting. The role requires automotive low-voltage harness and electrical architecture expertise, partner management across time zones, and proficiency with engineering change processes, risk analysis, and root-cause methodologies.

Develop and maintain embedded Linux operating systems and platform software for autonomous vehicle devices. Responsibilities include building scalable robotics infrastructure, managing Yocto and U-Boot systems, developing device drivers and kernel components in C, C++, or Rust, optimizing hardware-accelerated workloads, and supporting hardware bring-up, manufacturing, integration, and production deployment.

Develop and maintain embedded Linux operating system platforms and robotics infrastructure for autonomous vehicles. Responsibilities include building platform-level software, managing Yocto and U-Boot systems, developing device drivers and kernel components in C, C++, or Rust, optimizing hardware-accelerated workloads, and supporting hardware bring-up, manufacturing, integration, validation, and production deployment.

Own and scale Zoox’s software systems engineering pipeline ecosystem, including static analysis, sanitizers, CI enforcement, dashboards, and quality metrics. Develop tools and infrastructure, transition prototypes into production systems, troubleshoot cross-platform and determinism issues, support checker rollouts, document system designs, and collaborate with engineering leaders on milestones, incident reviews, and long-term software reliability.

Develop deep learning models using imitation and reinforcement learning to generate autonomous vehicle trajectories. Build production ML pipelines, metrics, and error-analysis tools; evaluate driving plans for safety, progress, and comfort; and collaborate with Planning, Perception, Simulation, and Systems Engineering teams to improve autonomous driving in complex urban environments.

Perform system safety analyses for autonomous vehicle sensing and perception systems. Define safety requirements, metrics, and fail-operational architectures for camera, lidar, radar, sensor fusion, and machine learning subsystems. Lead cross-functional safety projects, apply ISO 26262 and SOTIF methods, guide sensor architecture decisions, analyze field and simulation data, and support safety arguments for public-road deployment. The role also involves data analysis, system-level tradeoffs, and using AI/LLM tools to improve efficiency.

Leads architecture, optimization, scaling, and ownership of Zoox’s enterprise and AI data platform. Builds self-healing pipelines, governance frameworks, data quality and observability systems, secure access controls, lifecycle policies, and automated CI/CD deployment infrastructure. Optimizes Databricks and AWS EMR performance and costs while enabling low-latency, AI-ready data foundations. The role also drives enterprise security, compliance, schema evolution, and developer velocity, with opportunities to apply GenAI, Terraform, and EKS.

Develop distributed computing algorithms, performance metrics, and analysis tools for Zoox’s Collision Avoidance System. Analyze petabytes of urban driving data, evaluate system performance, and collaborate with CAS Perception, Planning, Systems Design, Mission Assurance, and QA engineers to define autonomous-driving validation metrics and plans.

Design and implement scalable, reliable full-stack web applications supporting autonomous robotaxi fleet monitoring and operations. Collaborate with product managers, designers, QA engineers, remote operators, and engineering teams to build features, improve existing systems, and optimize application performance, including latency, CPU and memory usage, and database queries. Contribute to in-vehicle visualization and real-time rider support tools while developing toward senior-level responsibilities.