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We are a world - class autonomous driving hardware and software development team. We have the best platform and have maintained a leading position in the field of artificial intelligence. Next, we will continue to deepen our efforts in the autonomous driving field and strive to bring sustained growth to our customers. NVIDIA is seeking a Principal Program Manager to build and operate product triage, performance analysis, and issue-closure operating system for autonomous driving programs. This is a key role to support AV software agile iteration & development for customer program release, together working with the engineering teams, understanding AV stack deeply and providing data-based judgement and delivering high-quality AV software to end customers.
Are you ready to handle sophisticated technical systems that deliver true self-driving capabilities to users? In this role, the candidate should be able to build scalable workflows, metrics, dashboards, operating rhythms, and team mechanisms that improve triage efficiency&accuracy in a scalable way, issue closure workflow, significant metric operations visibility, automation, and cross-functional accountability.
What you'll be doing:
Build and improve AV L2++/L3/L4 product and technical critical metric frameworks, track regressions, drive cross-functional corrective actions, and close validation loops to achieve measurable product performance improvement.
Define scalable AV triage strategy and process, build improve issue closure quality and efficiency, drive product/module performance improvements with cross-functional teams.
Lead triage/tagging automation and cross-functional issue closure across product, program, testing,.
Drive a structured issue-closure loop from critical metric regression to owner action, validation, closure, and regression prevention, improving product and module-level matrixs performance.
Define and improve AV product and technical matrixs frameworks, including metric definitions, failure modes/scenario-level matrixs regression gates, and validation criteria.
Define and improve the end-to-end AV product issue triage lifecycle, covering issue intake, tagging, classification, severity/priority assessment, owner routing, validation, closure, reopen, and regression tracking.
Build scalable triage workflows, taxonomies, quality-check, product performance dashboards, and operational metrics to improve triage consistency, closure efficiency, and critical metric visibility.
Establish KPI-to-issue traceability by connecting regressions to cases, failure modes, root causes, owner actions, validation outcomes, and measurable critical metric recovery.
Lead triage/tagging automation and cross-functional issue closure across product, program, testing, engineering, model/algorithm, simulation, evaluation, data, and operations teams.
What we need to see:
BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Automotive Engineering, Automation, or a related field, or equivalent experience.
15+ years proven ability in autonomous driving large scale in-car test, issue triage, system engineering, technical program management or related fields.
Strong experience on in-car test, product performance, issue triage, critical metric analysis, issue lifecycle management, validation analytics, or cross-functional issue closure.
Proven ability to drive cross-functional technical programs across carline programs, AD products, system engineering, model/algorithm, simulation, testing, fleet operations teams.
Strong experience building issue lifecycle processes, benchmark definition, Failure mode taxonomy, Scenario taxonomy, Root-cause taxonomy, Issue clustering, target dashboard, triage workflow, operating metrics, and issue-closure mechanism.
Ability to convert ambiguous product or testing signals into structured issues, failure patterns, root-cause hypotheses, owner actions, verification plans, and critical metric insights.
Team worker with excellent communication skills, including critical metric reporting, issue status reporting, risk summaries, and cross-functional closure updates.
