Senior Technical Program Manager, Autonomous Platform

NVIDIA Corporation

United States

On-site

USD 200,000 - 322,000

Full time

4 days ago
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Job summary

NVIDIA Corporation is seeking a Senior Technical Program Manager for the DRIVE AV Platform team. You will lead complex programs from embedded bring-up to production releases, coordinating across software, hardware, validation, and systems teams to deliver an automotive-grade autonomous driving platform.

You will translate deep embedded and platform knowledge into actionable roadmaps, manage risks, and drive scalable engineering processes with AI-enabled improvements.

Qualifications

  • 12+ years of proven experience in technical program management driving software engineering programs and releases.
  • Strong understanding of embedded software, OS fundamentals (Linux, QNX) and HW/SW integration.
  • Ability to translate deep technical detail into clear program roadmaps and executive updates.
  • Proven track record delivering large, scalable programs in fast-paced environments.

Responsibilities

  • Lead multiple complex programs across the autonomous driving platform from bring-up to production release.
  • Drive platform technologies across embedded OS, drivers, middleware, sensor integration, and validation.
  • Manage risks and dependencies across global engineering teams and deliver on milestones.
  • Improve processes for scalable engineering workflows, leveraging AI to optimize operations.

Skills

Embedded systems
Technical Program Management
Cross-functional collaboration
Communication
Agile/Scrum
Stakeholder management

Education

BS/MS in Computer Science or Electrical Engineering

Tools

Linux
QNX
Jira

Job description

NVIDIA Corporation is seeking a Senior Technical Program Manager for the DRIVE AV Platform team. You will lead complex programs from embedded bring-up to production releases, coordinating across software, hardware, validation, and systems teams to deliver an automotive-grade autonomous driving platform.

You will translate deep embedded and platform knowledge into actionable roadmaps, manage risks, and drive scalable engineering processes with AI-enabled improvements.

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