Staff Technical Program Manager - Autonomous Vehicle Platform
NVIDIA is hiring a Staff Technical Program Manager - Autonomous Vehicle Platform in Santa Clara, United States. It pays $200k-$322k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this role is Little AI ●○○○: aI is not part of the work.
- The posting mentions AI automation among its tools and skills.
- Level classes it as a lead role.
- NVIDIA has 2,700+ other open roles on Level.
- Posted in the last few days.
AI in this role
NVIDIA is defining the next era of computing, tapping into the unlimited potential of AI to power computers, robots, and self-driving cars that can understand the world. Our DRIVE platform gives automakers, Tier 1 suppliers, and start-ups the power and flexibility to develop and deploy breakthrough AI systems for autonomous vehicles — today powering over 270 partners in the development of autonomous cars, trucks, shuttles, and taxis.
We are looking for a deeply technical and experienced Senior Technical Program Manager to join the NVIDIA DRIVE AV Platform team. You will lead a focused effort to productize groundbreaking solutions that will redefine transportation and the growing field of self-driving cars. You will work shoulder-to-shoulder with dedicated multi-functional engineering teams across vehicle subsystems — software, hardware, validation, and systems — to integrate their work into our autonomous DRIVE SW platform, while achieving or exceeding all relevant NVIDIA and automotive standards and guidelines. What sets this role apart: you bring real software engineering depth, specifically in embedded systems and platform software, driving engineering teams with credibility, attention to detail, and AI automation. The work is exciting, impactful, and fast-paced. We have customers and competition.
What you'll be doing:
- Lead multiple, concurrent complex programs across the autonomous driving platform — from embedded platform bring-up through production release.
- Drive new platform technologies across the full stack: embedded OS, platform drivers, middleware, sensor integration, and validation.
- Run automotive software development and releases in a highly dynamic environment, maintaining quality across rapid release cadences.
- Translate deep embedded and SW knowledge into actionable program structures — defining scope, roadmaps, schedules, and milestones.
- Identify and resolve risks and issues that affect release scope, schedule, and quality, especially those spanning SW/HW boundaries.
- Identify and lead multi-functional dependencies proactively, including those spanning global engineering teams.
- Improve processes and procedures within the team; streamline day-to-day operations with an eye for scalable engineering workflow using AI.
- Communicate regularly with team members to set shared expectations and provide timely updates on progress, risks, and decisions.
What We Need to See
- BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).
- 12+ years of proven experience, with at least 8 years in Technical Program Management driving software engineering programs and releasing commercial products.
- Solid understanding of embedded systems software: OS fundamentals (Linux, QNX, or similar RTOS), platform drivers, sensor middleware, and SW/HW integration.
- Strong technical competence to engage deeply with engineering teams, debug program-level issues, and make sound trade-off calls across SW and HW domains.
- Consistent track record of delivering scalable, complex programs in fast-paced, multi-functional environments.
- Strong communication, organizational, and leadership skills — you can translate deep technical complexity into streamlined executive updates and drive alignment across large organizations.
Ways to stand out from the crowd:
- You have shipped embedded software in automotive, robotics, or a related domain to get software running reliably on constrained, safety-relevant hardware.
- Direct experience in autonomous vehicle platform development, including ADAS software integration, sensor fusion stacks, or platform validation.
- Familiarity with automotive-grade software standards (ISO 26262, ASPICE, or equivalent) and how they interact with program execution.
- Background leading global programs across time zones with geographically distributed engineering teams.
- Expertise in Agile and Scrum methodology; PMP or Scrum Master certification is a plus, with proficiency with Jira and PMP tools with agility and scale.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. If you want to help make autonomous vehicles a reality, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 200,000 USD - 322,000 USD for Level 5, and 240,000 USD - 379,500 USD for Level 6.You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until October 30, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.How we rate this
Staff Technical Program Manager - Autonomous Vehicle Platform at NVIDIA rates 25 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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