Responsibilities

• Own the global product marketing strategy and go-to-market for NVIDIA's real-to-sim and simulation frameworks portfolio, including the category narrative, positioning, messaging architecture, differentiation, audience strategy, and launch roadmap.
• Establish NVIDIA's leadership in redefining real-world observations into programmable, simulation-ready environments for Physical AI development.
• Drive messaging and go-to-market across real-world data capture, neural reconstruction and digital twins, open Physical AI datasets, classical and neural simulation frameworks, co-simulation, interoperability, and closed-loop testing.
• Build a cohesive developer narrative spanning capture, reconstruction, scene creation, simulation, training, testing, validation, and continuous improvement, articulating how classical and neural simulation combine physical accuracy, visual realism, scalability, and scenario diversity.
• Define the co-simulation story for connecting physics engines, neural world models, sensor simulation, autonomous-system software, and third-party simulation tools.
• Partner with product management, engineering, and research to influence portfolio strategy, roadmap priorities, platform integration, developer experience, and requirements across robotics, autonomous vehicles, vision AI, industrial automation, and other Physical AI domains.
• Drive developer adoption through reference architectures, technical content, demonstrations, workshops, sample workflows, hands-on experiences, open frameworks, shared scene and data standards, and reusable developer content.
• Develop strategic relationships and joint go-to-market programs with simulation companies, cloud providers, Physical AI developers, system integrators, research institutions, and open-source communities, and lead coordinated launches across developer relations, solution architects, business development, worldwide sales, corporate marketing, analyst relations, public relations, and investor relations.
• Develop executive messaging, define success metrics for developer activation and ecosystem growth, and represent NVIDIA with developers, researchers, customers, partners, analysts, media, and industry leaders.

Requirements

• Master's degree or equivalent experience in Engineering, Computer Science, Robotics, Artificial Intelligence, or a related technical field.
• 12+ years of proven experience in product marketing, technical product marketing, product management, developer relations, or a role in simulation, AI, robotics, autonomous systems, or developer platforms!
• Strong technical foundation in simulation, computer graphics, physics, AI, robotics, or autonomous systems, including real-to-sim pipelines, neural reconstruction, digital twins, sensor simulation, physics engines, neural world models, and co-simulation architectures!
• Experience developing go-to-market strategies for technical platforms, frameworks, SDKs, APIs, or open-source technologies.
• Demonstrated ability to build a unified market narrative across multiple technologies, development stages, and engineering audiences.
• Experience driving developer adoption through technical content, reference workflows, ecosystem programs, and community engagement.
• Ability to translate sophisticated technical capabilities into differentiated developer value and measurable business outcomes.
• Experience partnering with product management, engineering, and research to influence product strategy and roadmap.
• Outstanding written, verbal, and presentation abilities, with a consistent record to lead complex cross-functional initiatives across globally distributed technical, business, and executive teams.

Preferred

• Hands-on experience with simulation frameworks, digital twins, robotics, autonomous vehicles, computer vision, or synthetic data, including co-simulation, multi-physics simulation, software-in-the-loop, hardware-in-the-loop, or closed-loop testing.
• Familiarity with neural rendering, 3D Gaussian splatting, neural reconstruction, generative world models, or physics.
• Experience connecting multiple simulation engines, physics solvers, sensor models, and autonomous-system software stacks using open scene representations, data standards, and simulation interfaces.
• Background with building ecosystems around open-source frameworks, developer platforms, or industry standards.
• Experience crafting reference architectures, technical demonstrations, tutorials, workshops, or launch content, supported by published technical work, conference presentations, patents, or open-source contributions.

Benefits

• equity and benefits.