Nvidia Senior Product Manager Automotive AI - Autonomous Vehicles 

United States, California 

847876961

What you will be doing:

• Define top level product architecture and capabilities by synthesizing input from customers, government regulations, competitors benchmarking, and internal/external engineering teams

• Own the negotiation with customers on the feature roadmap and prioritization of capabilities

• Ensure use case definitions, system design, safety and other elements of the product are appropriately analyzed and aligned with the product goals.

• Own and Drive the end to end execution of the product through technical engagements (Architecture design, KPI reviews, etc) both internally and externally.

• Ensure the development is proceeding as planned and lead issue resolution when the development process is blocked.

• Develop product plan to ensure program schedules are adhered to and support maintaining a program risk open list

• Partner with the functional leaders across Product, HW, SW, Safety, Integration, Operations, as well as the customers to support their efforts in launching a successful product

• Be responsible for customer engagements to ensure alignment across all customers and support pre-sale discussions as needed

What we need to see:

• Strong solid understanding of ML/AI principles and technologies, with a focus on generative models.

• Experience with on-device or edge computing

• BS/MS (or equivalent experience) in engineering

• 8+ years of experience in both software and hardware platforms.

• You are a Self-starter, with a 'can-do' attitude in a multifaceted environment.

• Experience working in a software development environment

• Experience with product requirements management tools (e.g. JAMA)

• Track record of leading the launch of technically complex products to customers

• Strong technical leadership and communication skills, with the ability to drive alignment across large organizations and with customers

Ways to stand out from the crowd:

• Familiarity with NVIDIA’s technology stack, including CUDA, TensorRT, Omniverse, Cosmos, NIMs, or more

• Experience in deploying AI solutions in production environments.