The Role
Build the developer ecosystem for NVIDIA Dynamo, an open-source distributed AI inference framework. Responsibilities include creating demos, sample code, documentation, videos, technical talks, workshops, and office hours; collaborating with inference projects and open-source maintainers; troubleshooting deployments; gathering developer feedback; influencing engineering and product priorities; and communicating progress externally. The role requires hands-on experience with model serving, Kubernetes, distributed inference, performance optimization, and developer or partner programs.
Summary Generated by Built In
We are seeking a Senior Developer Relations Manager to build the developer ecosystem around NVIDIA Dynamo, our open-source framework for distributed AI inference. In this senior individual contributor role, you will help developers deploy and operate inference systems, build practical technical resources, and represent developer needs both in the community and inside NVIDIA!
What You'll Be Doing:
- Build the ecosystem with vLLM, SGLang, Mooncake, llm-d, and other inference projects through joint demos, integration guides, upstream contributions, and community programs that bring developers and maintainers together.
- Develop runnable demos, sample code, technical documentation, and videos that explain Dynamo’s modular ecosystem and demonstrate its data center performance value.
- Represent the developer community inside NVIDIA: turn feedback into concrete engineering and product requirements, influence priorities, and communicate progress back to developers.
- Advocate externally through technical talks, live demos, workshops, and office hours. Help developers troubleshoot real deployments and contribute to projects; track repeat participation, contributor growth, and issues resolved.
What We Need to See:
- Degree in Computer Science, Engineering, or a related field, or equivalent experience.
- 8+ years of overall technology industry experience, including 4+ years in AI/ML infrastructure, model serving, or distributed systems. Experience leading developer or partner programs across engineering, product, sales, marketing, and legal.
- A background in AI inference with practical experience deploying and managing model-serving systems: configuring deployments, monitoring latency and throughput, scaling capacity, and troubleshooting reliability or performance issues. Familiarity with inference engines such as vLLM, SGLang, or TensorRT-LLM, distributed serving stacks such as Dynamo or llm-d, and deploying and operating inference workloads on Kubernetes.
- Experience working with open-source maintainers through issues, pull requests, and design discussions, and translating developer feedback into technical priorities.
- A portfolio of technical guides, working demos, talks, or workshops you personally delivered that helped developers solve real problems. Ability to explain inference architecture and performance tradeoffs to audiences from engineers to executives.
Ways to Stand Out from the Crowd:
- A record of earning developer trust externally and influencing decisions internally—for example, a community-reported problem you carried through to a shipped fix, API improvement, or simpler deployment workflow.
- Experience working directly with the vLLM, SGLang, or Mooncake communities to co-create technical resources, recurring meetups, or hands-on workshops, with evidence of repeat participation, new contributors, and collaboration between projects.
- Ability to identify patterns in developer feedback, serving-stack choices, and emerging inference workloads, and translate them into recommendations for product roadmaps, ecosystem investments, and partner priorities.
NVIDIA is widely considered one of the technology world’s most desirable employers. We have some of the world's most forward-thinking and hardworking people on our team. . As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.You will also be eligible for equity and benefits.
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.Skills Required
- Degree in Computer Science, Engineering, a related field, or equivalent experience
- 8+ years of overall technology industry experience
- 4+ years of experience in AI/ML infrastructure, model serving, or distributed systems
- Experience leading developer or partner programs across engineering, product, sales, marketing, and legal
- Practical experience deploying and managing model-serving systems, including configuration, monitoring latency and throughput, scaling capacity, and troubleshooting reliability or performance issues
- Familiarity with inference engines such as vLLM, SGLang, or TensorRT-LLM
- Experience with distributed serving stacks such as Dynamo or llm-d
- Experience deploying and operating inference workloads on Kubernetes
- Experience working with open-source maintainers through issues, pull requests, and design discussions
- Ability to translate developer feedback into technical priorities
- Portfolio of technical guides, working demos, talks, or workshops personally delivered to solve real developer problems
- Ability to explain inference architecture and performance tradeoffs to engineers and executives
- Experience earning developer trust externally and influencing internal decisions
- Experience working directly with vLLM, SGLang, or Mooncake communities
- Ability to identify patterns in developer feedback and emerging inference workloads and translate them into product and ecosystem recommendations
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
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The Company
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
