Zoox has embarked on a highly ambitious journey to develop a full-stack autonomous mobility solution for our cities. As a technical program manager, you will work cross-functionally with engineering leaders across software, hardware, vehicle engineering, and product to drive our corporate strategy into tactical and detailed road maps that facilitate effective execution at each stage of our growth curve. You will work with each engineering team to develop project schedules, identify milestones, flag risks, estimate budgets, and clearly communicate ongoing progress.
In this role, you will:
Partner with Autonomy V&V engineering managers to translate the top-down corporate strategy and milestones into detailed product roadmaps, timelines, and deliverables
You'll drive and support teams of software engineers and data engineers/scientists to stand up cutting-edge evaluation pipelines leveraging statistics, simulation, and other methods
You'll play a defining role in building scalable systems that improve how we evaluate autonomy behavior at Zoox
You'll work with cross-functional stakeholders to proactively identify gaps, escalate risks, drive bug closure, and contribute to test coverage tracking
You'll be a trusted partner to engineering leadership and the go-to person for unblocking teams and driving solutions
Qualifications
BS/MS degree in computer science, engineering or equivalent job experience
At least 6 years of experience in engineering program management
Strong track record of managing complex cross-functional projects and problem-solving
An ability to keep the big picture in focus and to provide clear, well-structured, and concise communications tailored to each appropriate audience
Deep familiarity with software development processes & proficiency in tools or processes required to manage complex projects (i.e. Gantt charts, risk matrix, Smartsheet, JIRA, etc.)
Excellent written, presentation, and verbal communication skills are a must, ability to create visualizations of KPIs and program risks
Bonus Qualifications
Experience with AI/ML, autonomous vehicles, computer vision, large language models, reinforcement learning, simulation, and/or automotive or aerospace processes is highly desired
Experience working on complex safety-critical systems
