Developer Relations Manager, Higher Education and Research - Foundational AI

Posted Yesterday
Be an Early Applicant
Hiring Remotely in Santa Clara, CA, USA
In-Office or Remote
152K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Engage leading academic AI labs researching foundation models, LLMs, multimodal systems, reasoning, training, inference, and scalable AI infrastructure. Advise researchers on NVIDIA platforms, identify impactful workloads, track frontier research, translate academic feedback into product and platform opportunities, and support technical workshops, university programs, and research conferences. The role requires deep foundational AI expertise, hands-on experience with AI training or inference, and strong research engagement credibility.
Summary Generated by Built In

We are seeking a mission-driven Developer Relations Manager focused on Foundational AI Research to engage leading academic labs advancing the next generation of AI models, systems, and methods. In this role, you will work directly with top researchers building frontier AI systems, including large language models, multimodal models, reasoning systems, training methods, inference systems, model serving, and scalable AI infrastructure. You will help researchers adopt NVIDIA’s AI and accelerated computing platforms to push the boundaries of model performance, efficiency, and scale. The ideal candidate brings deep technical credibility in foundational AI, strong research engagement experience, and hands-on expertise in either AI inference research or AI training research.


What you'll be doing:

  • 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.

What we need to see:

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

Ways to stand out from the crowd:

  • Experience with NVIDIA AI platforms, including CUDA, CUDA-X libraries, TensorRT-LLM, Triton Inference Server, NIM, NeMo, Megatron, Transformer Engine, NCCL, DGX, NVLink, InfiniBand, or NVIDIA AI Enterprise.
  • Established relationships with leading AI labs, academic institutions, research institutes, benchmark communities, or major open-source AI projects.
  • Track record translating frontier AI research into demos, tutorials, reference architectures, workshops, technical blogs, or developer enablement programs.
  • Experience presenting at venues such as NeurIPS, ICML, ICLR, CVPR, AAAI , or related research workshops.
  • Ability to identify emerging research trends and convert them into strategic opportunities for collaboration, platform adoption, and ecosystem growth.

NVIDIA is widely considered to be one of the technology world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, 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.

Applications for this job will be accepted at least until September 25, 2026.

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, Applied Mathematics, Electrical Engineering, or a related technical field, or equivalent research experience
  • 5+ years of technology industry experience across software engineering, developer relations, technical partnerships, solutions architecture, or product management
  • 3+ years of hands-on AI experience
  • Deep expertise in foundational AI, including LLMs, multimodal models, generative AI, reasoning, post-training, model evaluation, or AI systems research
  • Strong understanding of pretraining, fine-tuning, post-training, optimization, evaluation, deployment, and model serving
  • Hands-on experience with AI research stacks such as 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 strategies, checkpointing, memory optimization, batching, scheduling, latency, throughput, and cost-performance tradeoffs
  • Familiarity with quantization, distillation, sparsity, speculative decoding, attention optimization, synthetic data generation, RLHF, RLAIF, and preference optimization
  • Ability to engage leading academic labs on frontier AI research challenges
  • Demonstrated research credibility through publications, open-source contributions, academic collaborations, technical leadership, or direct work on frontier AI systems
  • Experience with NVIDIA AI platforms and technologies
  • Established relationships with AI labs, academic institutions, research institutes, benchmark communities, or major open-source AI projects
  • Experience translating frontier AI research into demos, tutorials, reference architectures, workshops, technical blogs, or developer enablement programs
  • Experience presenting at NeurIPS, ICML, ICLR, CVPR, AAAI, or related research workshops

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.

  • 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.
  • 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.
  • 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

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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