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 engineering managers in the respective Autonomy team (Perception, Prediction & Behavioral ML, TeleGuidance, Planning & Controls, Collision Avoidance System) to translate the top-down corporate strategy and milestones into detailed product roadmaps, timelines, and deliverables
- Drive cross-functional teams across Autonomy teams to build and execute on solutions for improving our driving behavior
- Collaborate with engineering to figure out how best to develop the underlying measurements and datasets for Driving Behavior KPIs
- Highlight potential risks and proactively build out risk-mitigating actions
- Build and deliver executive presentations on program status, issues/risks, and accomplishments
Qualifications
- BS/MS degree in computer science, engineering or equivalent job experience
- At least 2 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 with developing and scaling strategy, processes, plans, procedures, reporting and handling escalations
- Strong references that highlight your ability to build strong working relationships with senior leaders, program managers, and engineers across functions and departments
Compensation and Benefits
There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. The salary will range from $140,000 to $278,000. A sign-on bonus may be part of a compensation package. Compensation will vary based on geographic location, job-related knowledge, skills, and experience.
Zoox also offers a comprehensive package of benefits including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.
About Zoox
Zoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team.
Accommodations
If you need an accommodation to participate in the application or interview process please reach out to
[email protected] or your assigned recruiter.
A Final Note:
You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.
