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:
- Experience with NVIDIA technologies and platforms such as CUDA, CUDA-X libraries, NVIDIA AI Enterprise, NIM, NeMo/Nemotron, BioNeMo, cuQuantum, Omniverse, Isaac, RAPIDS, TensorRT-LLM, Dynamo, or DGX/accelerated computing systems.
- Established relationships with leading academic labs, research institutes, national labs, or major open-source research communities.
- Track record translating frontier research into demos, reference architectures, workshops, technical content, or developer enablement programs.
- Experience presenting at academic conferences, research workshops, technical summits, or university facing events.
- Ability to identify emerging research trends and convert them into strategic opportunities for collaboration, platform adoption, and ecosystem growth.
With competitive salaries and a generous benefits package, we are widely considered to be one of the world's most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- 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 at the intersection of AI and science
- Deep expertise applying AI, including Generative AI and Physical AI, to a specific scientific domain
- Broad technical foundation across scientific fields such as biology, physics, materials 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, and sandboxed execution
- Established research credibility through high-impact publications, open-source scientific software contributions, or successful academic laboratory collaborations
- Experience with NVIDIA technologies and platforms such as CUDA, CUDA-X libraries, NVIDIA AI Enterprise, NIM, NeMo/Nemotron, BioNeMo, cuQuantum, Omniverse, Isaac, RAPIDS, TensorRT-LLM, Dynamo, or DGX systems
- Established relationships with academic labs, research institutes, national laboratories, or open-source research communities
- Track record translating frontier research into demonstrations, reference architectures, workshops, technical content, or developer enablement programs
- Experience presenting at academic conferences, research workshops, technical summits, or university-facing events
- Ability to identify emerging research trends and convert them into collaboration, platform adoption, and ecosystem growth opportunities
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
