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NVIDIA

Designs the chips and software that power AI

Developer Relations Manager - Multiple Teams

Developer Relations & AdvocacyConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • A BS, MS, or PhD in Engineering, Mathematics, Physics, Electronics, or Computer Science, or equivalent experience.
  • At least 4 years of work-related experience, especially with AI algorithms, datasets, and benchmarks, in a technical leadership role and architecting GPU-accelerated computing solutions.
  • Deep understanding of accelerated computing, AI for science, Agentic AI, physical AI, and the LLM ecosystem, including startups, ISVs, data stores, CSP services, and SaaS/platform offerings.
  • Strong analytical and problem-solving skills, with empathy for developers.
  • Clear written and oral communication skills and a proven track record of articulating value propositions to executive and technical audiences.
  • Strong project management skills, including planning, prioritizing, and driving multiple projects simultaneously while engaging internal and external stakeholders.
  • Extensive knowledge and experience with recent advancements in AI for Science, LLMs, VLMs, Agentic AI, and Physical AI.
  • A continuous learning mindset, self-direction, and focus on outcome-oriented activities.
  • Passion for AI and its continued development.

Responsibilities

  • Understand China’s researcher and developer communities, analyze technical requirements, and identify high-impact projects.
  • Bridge NVIDIA tools with community requirements and promote NVIDIA tools, libraries, and SDKs to China’s researcher and developer communities, ISVs, and service providers.
  • Apply deep understanding of AI algorithms, datasets, and benchmarks, including reinforcement learning for post-training; familiarity with widely used datasets, benchmarks, and leaderboard communities in general and vertical domains; and knowledge of related software ecosystems, performance-acceleration techniques, and AI-driven methodologies.
  • Discover new workflows, identify blockers to ISV adoption, and report findings to product teams.
  • Drive early adoption of new products and support launch and go-to-market activities.
  • Collaborate with NVIDIA business development managers, solution architects, developer technology engineers, developer marketing, product teams, customers, and communities.
  • Use conferencing tools and travel as needed to support partners.
  • Serve as a technical business development and accelerated-computing platform evangelist for researcher and developer communities.
  • Understand community requirements, analyze technical requests, integrate new or expand existing solutions, co-architect and advise on repeatable solutions, jointly scope project requirements for AI4S, GAI, Agentic AI, and Physical AI, and understand integrations with the ecosystem and private or hybrid platforms.
  • Support the AI algorithms, datasets, and benchmarks developer community.

Desired Qualifications

  • Experience developing with CUDA, operations research, AI4S models, robotics research, AI with database research, and ML/DL frameworks.
  • Background in community management, open-source communities, academic alliances, accelerated-computing development, LLM training/inference development, robotics, APIs and microservices, orchestration platforms, database solutions, and data migration techniques.
  • Hands-on experience enabling industry solutions for optimization scenarios covering logistics, supply chain, intelligent manufacturing, energy, and transportation.
  • Experience and empathy for software engineering and application development.
  • Strong technical background in AI algorithms, datasets, and benchmarking, particularly reinforcement learning for post-training, and deep familiarity with widely used datasets, benchmarks, and leaderboard ecosystems across general and vertical domains.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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