Customer Program Manager - Automotive

At NVIDIA, our employees are passionate about parallel and visual computing which is becoming the backbone of the recent Artificial Intelligence revolution.

We are searching for an experienced Customer Program Manager for the US market to lead the autonomous driving, robo-taxi, and AI in the car programs with Tier-1 and car OEMs.

Responsibilities:

• Lead customer-facing automotive programs involving AI, data science, ADAS, autonomous driving, in-cabin AI, perception, simulation, or software-defined vehicle platforms.
• Partner with customers and internal teams to define and execute data campaign initiatives, including data collection goals, sensor coverage, scenario targets, edge-case discovery, labeling needs, dataset readiness, and feedback loops into model development.
• Define program schedules, achievements, and work based on the customer roadmap and requirements.
• Translate customer requirements into specific tasks for all functional areas and actively collect, track, and drive all issues to closure.
• Communicate the issue status to the customer and internal teams located in different geographical zones.
• Identify and accurately represent the priority of issues and raise them appropriately.
• Work closely with the engineering, quality, logistics, and Sales team to resolve technical and logistic issues.
• Regularly communicate the program status and key issues to the customer and NVIDIA management.

Requirements:

• 12+ years of experience in project/program management in the Automotive or Embedded Industry for electrical/electronic and software products.
• A strong technical background and experience working with customers in an OEM environment.
• Experience in handling global projects with multinational program members.
• BS/MS or equivalent experience in Engineering or Computer Science, MBA with prior technical background.
• Understanding of machine learning and data science workflows, including data ingestion, labeling, feature analysis, model training, evaluation, validation, and deployment.
• Experience supporting or leading data campaign initiatives for automotive, robotics, autonomy, perception, mapping, simulation, or other AI-heavy domains.
• Exposure to ML Ops, data operations, cloud AI infrastructure, GPU-accelerated training, simulation pipelines, synthetic data, or large-scale data management.

Benefits:

• Equity
• Benefits