N

NVIDIA

Designs the chips and software that power AI

Director Simulation Product Management

Technical Product ManagementConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 12 years of product management experience, including a strong track record of delivering complex technical platform products at scale.
  • At least 4 years in a senior- or director-level product management role, with demonstrated experience leading and growing high-performing product management teams.
  • Deep understanding of autonomous driving development workflows, including sensor data pipelines, closed-loop simulation, synthetic data generation, and safety validation methodologies.
  • Hands-on familiarity with neural reconstruction, 3D Gaussian Splatting, or sensor simulation techniques, with the technical depth to engage credibly with research and engineering teams.
  • Ability to build multi-year product strategy in a fast-moving, high-ambiguity environment and drive cross-functional execution against that strategy.
  • Experience building developer or enterprise platform products, with an understanding of growing adoption through APIs, SDKs, and open ecosystems.
  • BSc or MSc in Computer Science, Electrical Engineering, Robotics, or a related technical discipline, or equivalent experience.

Responsibilities

  • Define and own the long-term product vision and roadmap for NVIDIA's autonomous vehicle simulation platform, spanning neural reconstruction (NuRec), generative simulation (Cosmos Sim), synthetic data generation (Cosmos Transfer), data curation (Cosmos Curator and Dataset Search), and closed-loop policy evaluation (AlpaSim).
  • Drive the end-to-end product lifecycle from requirements definition through engineering execution and customer adoption.
  • Build partnerships with OEMs, robotaxi operators, and autonomous vehicle software developers to understand simulation pipelines, identify unmet needs, and co-develop platform capabilities.
  • Partner with research and engineering teams to translate fleet data workflows, sensor modeling requirements, and policy evaluation needs into executable product requirements.
  • Establish and track product and ecosystem metrics, including scenario coverage, reconstruction fidelity, closed-loop evaluation throughput, and customer adoption; use them to guide prioritization and communicate progress to executive leadership.
  • Collaborate with go-to-market, developer relations, and solutions engineering to drive platform adoption, shape developer programs, and communicate the value of NVIDIA's simulation stack against competing approaches.
  • Lead, mentor, and grow a team of Product Managers focused on autonomous vehicle simulation, establishing best practices and raising product management standards across the organization.
  • Represent NVIDIA's simulation vision at industry events, safety and standards forums, and executive briefings, communicating its technical depth and strategic importance to engineering and business audiences.

Desired Qualifications

  • Direct experience owning or contributing to a simulation platform at an autonomous vehicle company, OEM, or autonomous vehicle software developer, ideally across scene reconstruction through closed-loop evaluation.
  • Working knowledge of NVIDIA's autonomous vehicle simulation ecosystem, including NuRec, Cosmos, AlpaSim, or the Alpamayo model family.
  • Familiarity with sim-to-real transfer challenges and techniques such as domain randomization, neural rendering, and real-to-sim pipelines.
  • Experience with reinforcement learning workflows in simulation, including policy post-training and closed-loop reinforcement learning frameworks such as AlpaGym.
  • A track record of building developer ecosystems around simulation or physical AI platforms, including open-source programs, partner integrations, and community-driven adoption.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

Recently Posted Jobs

Explore more opportunities at NVIDIA

See more jobs