Developer Relations Manager, Higher Education and Research, Foundational AI

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $152,000–$241,500 / yr
Posted: 114 days ago
Freshness: Confirmed live yesterday

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $238k

This role $197k

$136k most similar roles pay here $298k

This role pays less than 73% of similar roles. Most pay $196,750–$279,825 — the shaded band above. At the midpoint, this role pays about $197k versus about $238k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Developer Relations Manager, Higher Education and Research, Foundational AI

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Developer Relations Manager, Higher Education and Research - Foundational AI serves as a technical advisor to academic labs developing frontier AI systems, including large language models, multimodal models, reasoning systems, and scalable infrastructure. The role involves identifying high-impact research workloads where accelerated computing platforms can improve model performance and efficiency while translating academic feedback into actionable product insights. You will engage with principal investigators and researchers to address technical blockers and track emerging trends across papers and open-source projects. Required expertise includes foundational AI, PyTorch, JAX, distributed training frameworks, and inference systems. Candidates must possess deep knowledge of quantization, distillation, RLHF/RLAIF, and GPU-accelerated workflows. The role focuses on the specific domain of advancing model scale, performance, and optimization within the academic research landscape for next-generation AI models and serving technologies.

Skills

LLMs Multimodal Models PyTorch JAX CUDA TensorRT-LLM Triton Inference Server NeMo Megatron Transformer Engine NCCL Distributed Training Quantization RLHF RLAIF Inference Systems Model Serving InfiniBand

What you'll do

Act as a technical advisor to academic labs developing foundation models, LLMs, and multimodal systems.
Identify high-impact research workloads where NVIDIA software and hardware can improve model performance and scale.
Engage with principal investigators and researchers to identify technical blockers and infrastructure needs.
Track frontier AI trends across papers, benchmarks, and open-source projects to identify future platform opportunities.
Translate academic feedback into actionable insights for internal product roadmaps and developer programs.
Support NVIDIA’s presence at major AI research venues through technical content, workshops, and university engagements.
Drive researcher adoption of NVIDIA's accelerated computing platforms and software stacks.

What we're looking for

PhD in Computer Science, AI, Machine Learning, Applied Mathematics, Electrical Engineering, or a related technical field.
5+ years of experience in the field.
Deep expertise in foundational AI including LLMs, multimodal models, generative AI, and reasoning systems.
Hands-on experience with research stacks like PyTorch, JAX, distributed training frameworks, and GPU-accelerated workflows.
Technical fluency in scalable AI systems including distributed training, parallelism strategies, and memory optimization.
Familiarity with model efficiency methods such as quantization, distillation, sparsity, and RLHF/RLAIF.
Demonstrated research credibility through publications, open-source contributions, or technical leadership.
Experience engaging academic labs and translating frontier research into demos, tutorials, or developer programs.

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