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NVIDIA
NVIDIA
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NVIDIA develops accelerated computing and artificial intelligence technologies used across gaming, data centers, cloud computing, healthcare, manufacturing, automotive, and robotics. Its work spans graphics processing units, AI platforms, simulation, and industry-focused solutions, including NVIDIA Omniverse for collaborative 3D workflows, NVIDIA DRIVE for autonomous vehicle development, and NVIDIA Clara for healthcare applications. The company brings together large technical teams working on the infrastructure and software that support advanced computing, simulation, and AI-driven analytics.
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NVIDIA Developer Relations Manager – Foundational AI Research (Remote, California)

Lead technical engagement with academic researchers advancing foundation models and AI systems. Connect frontier research in training, inference, and scalable computing with NVIDIA platforms and developer programs.

USUnited StatesCACalifornia
$152,000 – $241,500 / year
RemoteFull-timeMiddleSeniorEnglish RequiredDeveloper Relations
PyTorch

Description

  • Advise leading academic AI laboratories on foundation models, large language models, multimodal AI, reasoning, training, inference, and AI systems.
  • Find high-value research workloads where NVIDIA software, systems, and accelerated computing can improve model performance, scalability, and efficiency.
  • Work with principal investigators, postdoctoral researchers, graduate students, and lab leaders to understand research priorities, technical obstacles, infrastructure requirements, and collaboration opportunities.
  • Monitor frontier AI developments across research papers, benchmarks, open-source projects, and academic laboratories to uncover emerging trends and platform opportunities.
  • Collaborate with Research Account Managers, Solution Architects, Product, Engineering, and Business Development teams to encourage researcher adoption and build lasting relationships.
  • Convert academic feedback into practical input for product roadmaps, developer initiatives, educational programs, and platform strategy.
  • Represent NVIDIA at leading AI, machine learning, and systems research venues through technical content, workshops, university partnerships, and programs for research laboratories.

Requirements

  • PhD in Computer Science, artificial intelligence, machine learning, applied mathematics, electrical engineering, or a related technical discipline, or equivalent research experience.
  • At least five years in the technology industry across software engineering, developer relations, technical partnerships, solutions architecture, or product management, including at least three years of hands-on AI experience.
  • Advanced knowledge of foundational AI, including large language models, multimodal models, generative AI, reasoning, post-training, model evaluation, or AI systems research.
  • Strong grasp of the AI development lifecycle, including pretraining, fine-tuning, post-training, optimization, evaluation, deployment, and model serving.
  • Hands-on experience with research tools and platforms such as PyTorch, JAX, distributed training frameworks, inference systems, model-serving platforms, evaluation pipelines, and GPU-accelerated workflows.
  • Technical understanding of scalable AI infrastructure, including distributed training, parallelism, checkpointing, memory optimization, batching, scheduling, latency, throughput, and cost-performance tradeoffs.
  • Familiarity with techniques for improving model efficiency and quality, including quantization, distillation, sparsity, speculative decoding, attention optimization, synthetic data generation, RLHF/RLAIF, and preference optimization.
  • Ability to discuss frontier research challenges with leading academic laboratories, including scaling behavior, compute efficiency, model quality, benchmark design, reproducibility, reliability, and research impact.
  • Evidence of research credibility through publications, open-source work, academic collaborations, technical leadership, or direct contributions to advanced AI systems.
  • Experience with NVIDIA AI technologies such as CUDA, CUDA-X libraries, TensorRT-LLM, Triton Inference Server, NIM, NeMo, Megatron, Transformer Engine, NCCL, DGX, NVLink, InfiniBand, or NVIDIA AI Enterprise.
  • Established connections with leading AI laboratories, universities, research institutes, benchmark communities, or major open-source AI projects.
  • Proven ability to turn advanced AI research into demonstrations, tutorials, reference architectures, workshops, technical articles, or developer enablement programs.
  • Experience presenting at conferences or workshops such as NeurIPS, ICML, ICLR, CVPR, AAAI, or comparable research venues.
  • Ability to recognize emerging research directions and translate them into collaboration, platform adoption, and ecosystem opportunities.

Benefits

  • Equity
  • Benefits

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