Developer Relations Manager, Higher Education and Research - Foundational AI

NVIDIA Gruppe; Santa Clara (CA); On-site; USD 152,000 - 241,500; Full time

Job summary

NVIDIA Gruppe in Santa Clara is seeking a Developer Relations Manager focused on Foundational AI Research. In this role, you'll engage with leading academic labs to advance AI models, systems, and methods.

Your responsibilities include identifying high-impact workloads for NVIDIA's platforms and supporting researcher adoption. Candidates should have a PhD and 5+ years in AI, with expertise in large language models and research credibility through publications or collaborations.

Qualifications

• PhD in Computer Science, AI, Machine Learning or related field.
• 5+ years of experience in AI research.
• Deep expertise in foundational AI including LLMs.

Responsibilities

• Serve as a trusted advisor to academic AI labs.
• Identify research workloads for NVIDIA platforms.
• Engage with researchers to understand their technical needs.

Skills

Foundational AI

Machine Learning

Large Language Models

Data Evaluation

Education

PhD in Computer Science or related field

Tools

PyTorch

JAX

CUDA

Job description

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.

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 a related technical field, or equivalent research depth.
• 5+ years of experience in the field.
• 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 pre-training, fine-tuning, post-training, optimisation, 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 optimisation, batching, scheduling, latency, throughput and cost-performance trade-offs.
• Familiarity with methods that improve model efficiency and performance, such as quantisation, distillation, sparsity, speculative decoding, attention optimisation, synthetic data generation, RLHF/RLAIF and preference optimisation.
• Ability to engage top academic labs on frontier research challenges, including scaling behaviour, 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

• 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.

Compensation: Base salary range for Level 3 is $152,000 – $241,500, and for Level 4 is $184,000 – $287,500. Eligible for equity and benefits.

NVIDIA is committed to fostering a diverse work environment and is proud to be an equal-opportunity employer. We do not discriminate on the basis of race, religion, colour, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.