Developer Relations Manager, Higher Education and Research – AI for Science

We are seeking a dynamic, mission-driven Developer Relations Manager to engage leading university-affiliated researchers and labs. In this role, you will work directly with researchers to accelerate the adoption of NVIDIA’s sophisticated AI and computing platforms.

The ideal candidate combines deep technical expertise with strong experience in research engagement and proven track record to translate advanced technologies into valuable, insight-focused outcomes.

What you'll be doing:

• Act as a trusted technical advisor for research labs, engaging and partnering with ecosystem leaders, identifying and accelerating high-impact workloads by integrating NVIDIA's frameworks, libraries, and core software stack into research projects.
• Map and continuously assess the research ecosystem to identify institutional growth opportunities and inform long-term technology strategies .
• Stay current on research papers across affiliated domains to anticipate emerging trends and provide technical direction on future collaboration areas.
• Collaborate cross-functionally with Research Account Managers, Solution Architects, and Business Development teams to drive researcher enablement
• Forge closer ties with lab personnel, understanding opportunities, challenges, interpersonal dynamics and the full scope of research being conducted.
• Attend domain scientific conferences and facilitate NVIDIA participation alongside other subject matter experts. Drive success stories into adoption
• Represent the needs of researchers internally by translating academic feedback into actionable insights that build product development, education programs, and platform roadmaps.

What we need to see:

PhD in Computer Science, AI, Machine Learning, Computational Science or a related technical field; or equivalent experience demonstrating comparable research depth.

Over 4+ years of experience in research or industry, with a proven record of advancing innovation at the crossroads of AI and Science.

Deep expertise in applying AI, including Generative AI and Physical AI, to a specific scientific domain is required. A broad intellectual foundation is also necessary to translate AI breakthroughs across fields such as Biology, Physics , material science and complex scientific workflows.

Strong understanding of frontier research challenges in AI and computational science.

Hands-on experience building or evaluating AI systems using modern frameworks, model APIs, orchestration tools, retrieval systems, sandboxed execution for research-grade deployment.

Established research credibility evidenced by high-impact publications, contributions to open-source scientific software, or successful collaborations with academic laboratories.

Ways to stand out from the crowd: