# Global Account Manager, Developer Relations - Meta at NVIDIA

NVIDIA is hiring a Global Account Manager, Developer Relations - Meta in Santa Clara, United States. It pays $224k-$357k a year and Level rates it Works on AI ●●●○; you can [apply on NVIDIA](https://jobsbylevel.com/go/0696df83-8248-42a4-9d43-6f5de588794d?utm_medium=ai-agent).

AI Level 3, AI centrality 71 out of 100. US, CA, Santa Clara.

## Details

- Company: [NVIDIA](https://jobsbylevel.com/companies/nvidia)
- AI level: AI Level 3 (score 71 out of 100)
- Location: US, CA, Santa Clara
- Salary: $224k-$357k
- Posted: August 3, 2026
- Apply: https://jobsbylevel.com/go/0696df83-8248-42a4-9d43-6f5de588794d?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=global-account-manager-developer-relations-meta-at-nvidia-a571c5

## Prepare for this job

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## Description

As a Global Account Manager, Developer Relations, you'll be responsible for the technical charter for expanding integration of NVIDIA's libraries and frameworks across one of our largest and most strategic partners. You will work with teams across NVIDIA and Meta to drive the integration of NVIDIA's libraries and frameworks into Meta’s platforms, aligning with their long-term business and technical goals. This highly visible position works with our product and engineering organization to deliver joint solutions that move the needle, and extends that impact through the technologies and projects the partner stewards. The ideal candidate brings an outstanding blend of Meta ecosystem and large-scale AI infrastructure proficiency, a deep passion for developer advocacy, and strong technical account management experience. What you’ll be doing: Drive adoption of NVIDIA software libraries and frameworks across business, product, engineering, and research teams Work closely with the NVIDIA account, developer relations, solutions architecture, and developer technology teams on product and engineering integration priorities and coordination Accelerate critical workloads by demonstrating and integrating the NVIDIA software stack into partner products, platforms, and pipelines. Guide and support the partner in integration by bringing NVIDIA's developer technology, engineering, solutions architecture and product resources to accelerate adoption and foster co-engineering of next-generation solutions Engage technical leaders to drive best-practice integrations and resolve technical challenges, using regular syncs to track adoption, surface new workflows, and channel critical field insights back to NVIDIA product teams Build strong relationships with executive and technical collaborators across partner organizations — from C-suite sponsors to the developers building production software Advocate for NVIDIA software within partner’s executive leadership, architect, research and developer communities, driving early adoption of new tools, libraries, frameworks, and SDKs Identify integration opportunities to deliver differentiated solutions and unique value propositions — particularly in inference optimization, model training, recommender systems, kernel-level performance, and data processing Champion partner’s needs and perspectives within NVIDIA, influencing product strategy and roadmap Act as NVIDIA's PIC (Pilot in Command) to lead cross-functional teams — including product management, engineering, solutions architects, developer relations, marketing, legal, sales, and ecosystem teams — ensuring partnership success Grow adoption of NVIDIA libraries and frameworks upstream in the open-source projects the partner maintains and contributes to, and support downstream adoption across the ecosystem What we need to see: Bachelor's degree in Computer Science, Engineering, Electrical Engineering, or a related field, or a Master's degree or equivalent experience 12+ years of overall professional experience in the technology industry in developer relations, product management, technical partnerships, business development, solutions architecture, or systems and performance engineering, including 3+ years of direct hands-on experience in inference serving and efficiency improvements, machine learning model development, recommendation algorithms and ranking at scale, GPU kernel development, AI/ML software development, or data processing Deep understanding of large-scale AI infrastructure — frontier model training and inference platforms, recommender and ranking systems, data processing platforms — and the software stack that runs them Technical depth sufficient to engage partner research and performance engineering teams as a peer — able to reason about model architecture, kernel and attention implementations, distributed training and inference, and performance tradeoffs Consistent record to structure and drive progress of complex technical engagements,

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