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 other objective job-related factors. The expected base salary ranges for this position are:
- 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 November 3, 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.
