NVIDIA
Global Account Manager, Developer Relations - Meta
$224K–$431K
US, CA, Santa Clara +1 · Manager · Full-time · Posted Aug 3, 2026
- Location
- US, CA, Santa Clara
US, Remote - Experience
- 12+ years of overall professional experience in the technology industry, including 3+ years of direct hands-on experience in one or more specified AI, inference, recommendation, GPU kernel, or data-processing areas.
- Education
- Bachelor's degree in Computer Science, Engineering, Electrical Engineering, or a related field, or a Master's degree or equivalent experience.
About the job
Leads NVIDIA–Meta technical partnerships to integrate NVIDIA libraries and frameworks across Meta platforms, accelerate adoption, and deliver joint solutions.
What you'll do
- Drive adoption and integration of NVIDIA software across Meta’s business, product, engineering, and research teams.
- Coordinate cross-functional teams to advance integration priorities, resolve technical challenges, and develop joint solutions.
- Represent partner needs within NVIDIA and grow adoption in open-source projects and across the ecosystem.
What they ask for
- Bachelor's degree in Computer Science, Engineering, Electrical Engineering, or a related field, or a Master's degree or equivalent experience.
- Deep understanding of large-scale AI infrastructure and its software stack.
- Technical depth to engage with research and performance engineering teams on model architecture, kernels, distributed training and inference, and performance tradeoffs.
- Experience influencing partner product roadmaps and driving complex technical engagements.
Nice to have
- MBA or MS or PhD in computer science, electrical engineering or similar field.
- Familiarity with NVIDIA software libraries and platforms, open-source projects, AI research organizations, or Meta.
Pay
224,000 USD - 356,500 USD base salary; 272,000 USD - 431,250 USD base salary
Tools
CUDA-X, CUTLASS, CuTeDSL, cuEmbed, cuVS, cuDF, NCCL, TRT-LLM
AI focus
Supports integrations and adoption involving frontier model training and inference, inference optimization, recommender systems, ranking, GPU kernels, and data processing.
Model-written summary · the original posting is authoritative