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Developer Relations Manager, Foundational AI (Higher Education and Research)

NVIDIA· Account Mgr, Dev Relations
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Hybrid (Santa Clara, CA), Remote$152k - $241.5kFull-timePosted 4w ago

About the role

Developer Relations Manager focused on Foundational AI Research to engage leading academic labs, helping researchers adopt NVIDIA’s AI platforms to advance foundation models, AI systems, and scalable infrastructure.

Responsibilities

  • Serve as a trusted technical advisor to leading academic AI labs working on foundation models, LLMs, multimodal AI, reasoning, training, inference, and AI systems.
  • Identify high-impact research workloads where NVIDIA software, systems, and accelerated computing platforms can advance model performance, scale, and efficiency.
  • Engage principal investigators, postdocs, graduate researchers, and lab leadership to understand research goals, technical blockers, infrastructure needs, and collaboration opportunities.
  • Track frontier AI research across papers, benchmarks, open-source projects, and academic labs to identify emerging trends and future platform opportunities.
  • Partner with Research Account Managers, Solution Architects, Product, Engineering, and Business Development teams to support researcher adoption and long-term engagement.
  • Represent researcher needs internally by translating academic feedback into actionable insights for product roadmaps, developer programs, education, and platform strategy.
  • Support NVIDIA participation in major AI, ML, and systems research venues through technical content, workshops, university engagements, and lab-facing programs.

Qualifications

  • PhD in Computer Science, AI, Machine Learning, Applied Mathematics, Electrical Engineering, or related technical field, or equivalent research experience.
  • 5+ years of experience in technology across software engineering, developer relations, technical partnerships, solutions architecture, or product management, including 3+ years hands-on in AI.
  • Deep expertise in foundational AI (LLMs, multimodal models, generative AI, reasoning, post-training, model evaluation) or AI systems research.
  • Strong understanding of modern AI model development lifecycle (pretraining, fine-tuning, post-training, optimization, evaluation, deployment, model serving).
  • Hands-on experience with AI research stacks (PyTorch, JAX), distributed training frameworks, inference systems, model serving platforms, evaluation pipelines, and GPU-accelerated workflows.
  • Technical fluency in scalable AI systems (distributed training, parallelism, checkpointing, memory optimization, batching, scheduling, latency, throughput, cost-performance).
  • Familiarity with efficiency/improvement methods (quantization, distillation, sparsity, speculative decoding, attention optimization, synthetic data, RLHF/RLAIF, preference optimization).
  • Ability to engage top academic labs on frontier research challenges (scaling, compute efficiency, model quality, benchmarks, reproducibility, impact).
  • Demonstrated research credibility via publications, open-source contributions, academic collaborations, technical leadership, or direct work on frontier AI systems.

Skills

Required:Foundational AI expertiseAI research stacksLifecycle AI model developmentScalable AI systemsAcademic relationship management
Nice to have:Research communicatie & advocacy

Benefits

  • Equity
  • Benefits detailed at NVIDIA benefits page (link provided in job description)
Last updated Sep 25, 2026. Interested? Apply on the company site.

About NVIDIA

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NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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