Used Tools & Technologies
Machine Learning LLMRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
GitHub @ 3
Communication @ 6
API @ 3
CUDA @ 3
GPU @ 3
Codex @ 5
Claude Code @ 5
AI @ 3
HPC @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is building the leading platform for Quantum Computing with CUDA-Q. In this role you will drive technical enablement across a broad developer ecosystem — creating content, tools, and experiences that help quantum researchers, HPC practitioners, and AI developers get hands-on with CUDA-Q. You will work at the intersection of quantum computing, accelerated computing, and AI to ensure that the people building the next generation of quantum applications have everything they need to succeed.
Responsibilities
- Analyze developer journey needs with product teams and domain experts to identify and close gaps for both human and agent workflows using CUDA-Q
- Define practical standards for developer surfaces including GitHub, docs, example code, and onboarding that work for both developers and the AI agents they use
- Create MCP servers, Agent Skills, API documentation patterns, agent-consumable tests, and prompt-ready templates
- Build and maintain enablement resources — templates, runbooks, checklists, context files, and reference implementations — that quantum researchers and developers can use directly
- Evaluate content performance using human engagement metrics and agent signals to continuously improve developer time-to-value with CUDA-Q
- Define success criteria and evaluation frameworks for agentic developer tools — designing benchmarks, running evals, and translating results into actionable product improvements
- Track emerging AX, GEO, and AI citation research and translate findings into practical guidance for teams building quantum computing applications
Requirements
- Bachelor’s degree in a technical field, or equivalent experience
- 5+ years of related work experience
- Experience with documentation systems, information architecture, and content strategy for developer-facing and agent-facing technical content
- Understanding of agent-consumable content standards such as llms.txt, MCP, Agent Skills, and API documentation patterns
- Knowledge of quantum computing concepts and familiarity with CUDA-Q or similar quantum computing frameworks
- Proficiency with agentic coding harnesses such as Claude Code or Codex, and the judgment to evaluate AX tooling — from MCP servers and Agent Skills to API docs and prompt templates — for different contexts
- Strong communication and interpersonal skills, with the ability to collaborate effectively with researchers, engineers, and product teams
- Experience designing evaluations for developer or ML products — controlled experiments, human eval pipelines, or benchmark harnesses — with clear success criteria defined upfront
- A track record of staying ahead of fast paced technology shifts and translating findings into practical guidance
Ways to stand out
- Hands-on experience with CUDA-Q or other quantum computing frameworks, and an intuition for how quantum workloads connect to the broader GPU-accelerated computing stack
- Track record of building enablement resources — libraries, playbooks, templates — that developer teams actually use, and driving adoption across organizations
- Contributions to open-source quantum computing, AI, or developer tooling projects
- Experience using data and analytics to measure developer onboarding, identify friction points, and drive improvements
Additional information
- Base salary ranges (location and level dependent):
- Level 3: 136,000 USD - 212,750 USD
- Level 4: 160,000 USD - 253,000 USD
- You will also be eligible for equity and benefits.
- Applications for this job will be accepted at least until July 5, 2026.
- NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.