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

Lead systems engineering work to define and measure critical driving behaviors, develop metrics, provide verification requirements, anticipate risks, and drive cross-functional projects to improve autonomous vehicle system performance and reliability.

Leads Waymo’s Collision Avoidance Testing Team, including hiring, goal-setting, technical direction, and career development. Partners with planning, perception, systems, safety, simulation, and tooling teams to develop scalable, maintainable, and extensible autonomous-vehicle behavioral testing frameworks. The role requires building scalable testing programs, guiding architecture for long-tail behavioral testing, and delivering safety-critical engineering impact.

Build and evolve mission-critical backend infrastructure and commercialization tools for Waymo’s autonomous vehicle fleet. Collaborate with Product, Security, and engineering teams to develop secure systems, including vehicle configuration, secure parts transactions, key provisioning, and security infrastructure. Apply backend engineering, microservices, cryptography, PKI, authentication, encryption, and access-control expertise to solve business-critical problems.

Analyze large-scale autonomous driving and simulation data to develop safety and driving-quality metrics, statistical models, predictive features, and machine-learning methodologies. Build repeatable data analysis and reporting pipelines in collaboration with engineering teams. The role requires pursuing a quantitative PhD, programming proficiency in Python or R, and strong statistical theory. Preferred qualifications include machine learning, SQL or C/C++, high-dimensional data experience, research publications, foundation-model expertise, and autonomous-driving or generative-AI internship experience.

Train and fine-tune multi-task transformer models for autonomous driving using JAX/Flax on TPUs. Build data and evaluation pipelines, conduct rigorous model evaluations, contribute production-quality code, and communicate findings through design documents and presentations. Collaborate with engineering, data science, and evaluation stakeholders.

Leads the global transformation and scaling of Waymo’s partner and enterprise support organization. Oversees 24/7 multilingual support operations, organizational design, resource forecasting, KPIs, quality governance, safety-critical workflows, regulatory compliance, incident response, and Voice of the Partner insights. Partners with Product, Engineering, Safety, vendors, and other stakeholders to deploy automation and AI-driven support solutions across autonomous vehicle operations.

Build and lead the Vehicle Realism Platform for Waymo’s autonomous-driving simulator. Design scalable architectures, improve simulator reliability and reproducibility, bridge vehicle subsystems with simulation infrastructure, and deliver realistic simulation solutions across hardware platforms. Collaborate with robotics, onboard, hardware, evaluation, and simulator teams. The role requires backend development, production monitoring, systems programming, C++, and experience building products in distributed environments.

PhD intern will improve causal and predictive pricing models using feature engineering, regularization, time series estimation, and loss quantification. The role involves applying causal inference, econometrics, predictive modeling, Python, and SQL to support pricing decisions and operational efficiency at an autonomous driving company.

Drive cross-functional execution of onboard autonomous driving and machine learning programs. Manage schedules, risks, dependencies, milestones, and stakeholder communications across engineering, research, product, and release management. Contribute to strategic planning and technical roadmaps for foundation models, resolve roadblocks, and report program progress and KPIs to leadership. The role requires technical program management experience in software environments and familiarity with machine learning models, training pipelines, and evaluation frameworks.

Conduct exploratory research, evaluate theories statistically, present findings to focus groups, and design and implement software. The intern will work on autonomous driving technology while collaborating with technical teams. Required qualifications include current PhD enrollment in computer science or a related technical field, Python programming fluency, statistical knowledge, and basic machine learning knowledge.