NVIDIA
Senior Manager, Developer Relations - Higher Education and Research
$272K–$431K
US, CA, Santa Clara · Manager · Full-time · Posted Aug 27, 2026
- Experience
- 12+ overall years of industry and research experience, including 4+ years managing teams in developer relations, research engagement, or technical partnerships.
- Education
- PhD in Computer Science, AI, Machine Learning, Computational Science, or a related technical field, or equivalent experience.
About the job
Lead NVIDIA’s US higher-education and research developer-relations efforts, building a team and driving adoption of NVIDIA platforms across academic research.
What you'll do
- Manage and mentor Developer Relations Managers covering AI for science and set team direction.
- Develop researcher-engagement strategy and build relationships with academic and research stakeholders.
- Promote NVIDIA’s research platform, lead conference and university programs, and coordinate across internal teams to translate researcher feedback into product and program insights.
What they ask for
- PhD in Computer Science, AI, Machine Learning, Computational Science, or a related technical field, or equivalent experience.
- 12+ years of industry and research experience, including 4+ years managing teams in developer relations, research engagement, or technical partnerships.
- Deep technical proficiency in foundational AI and AI for science.
- Track record engaging senior research stakeholders and driving platform adoption through technical enablement, community programs, and cross-functional collaboration.
Nice to have
- Publications, open-source contributions, or direct experience with leading AI systems or AI-based scientific solutions.
- Hands-on NVIDIA technology experience, research ecosystem relationships, scientific-domain expertise, or experience navigating a complex global organization.
Pay
272,000 USD - 431,250 USD (base salary)
Tools
CUDA, NeMo, BioNeMo, PhysicsNeMo, Earth-2, Omniverse, RAPIDS, TensorRT-LLM
AI focus
Lead developer relations and platform adoption for frontier AI research and AI for science, spanning LLMs, training, post-training, inference, scientific computing, simulation, and domain-specific scientific AI applications.
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