Technical Marketing Engineer, CUDA-Q Developer Enablement

Nvidia

Confirmed live 2 days ago High trust

Remote

Quick summary

Work type: Remote
Location: Canada
Salary: $136,000–$212,750 / yr
Posted: 72 days ago
Freshness: Confirmed live 2 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $206k

This role $174k

$123k most similar roles pay here $258k

This role pays less than 78% of similar roles. Most pay $177,250–$235,750 — the shaded band above. At the midpoint, this role pays about $174k versus about $206k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

Most-posted roles

View all roles at Nvidia

At a glance

TL;DR · Technical Marketing Engineer, CUDA-Q Developer Enablement

Role Posting Log in to save

As a Technical Marketing Engineer — CUDA-Q Developer Enablement, you will join the team building the leading platform for Quantum Computing with CUDA-Q. You will drive technical enablement across a broad developer ecosystem by creating content, tools, and experiences for quantum researchers, HPC practitioners, and AI developers. Your daily responsibilities include analyzing developer journey needs, defining standards for GitHub surfaces, and building enablement resources like runbooks, checklists, and reference implementations. You will develop MCP servers, Agent Skills, and prompt-ready templates while evaluating content performance through human engagement metrics and agent signals. The role requires expertise in information architecture, content strategy, and quantum computing concepts. You will utilize tools such as Claude Code or Codex while navigating the intersection of quantum computing, accelerated computing, and AI to solve complex problems for those building next-generation quantum applications.

Skills

CUDA-Q Quantum Computing Accelerated Computing AI MCP GitHub API Documentation LLMs Claude Code Codex Information Architecture Content Strategy Benchmark Harnesses

What you'll do

Identify and close gaps in developer journey needs for both human and agent workflows using CUDA-Q.
Define standards for developer surfaces including GitHub, documentation, example code, and onboarding processes.
Create MCP servers, Agent Skills, API documentation patterns, and prompt-ready templates for AI agents.
Build and maintain enablement resources such as runbooks, checklists, and reference implementations for quantum researchers.
Evaluate content performance using human engagement metrics and agent signals to improve developer time-to-value.
Define success criteria and evaluation frameworks for agentic developer tools through benchmarks and evals.
Track emerging AI citation research and translate findings into practical guidance for quantum computing applications.

What we're looking for

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 and agent-facing 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 frameworks.
Proficiency with agentic coding harnesses like Claude Code or Codex to evaluate AX tooling.
Experience designing evaluations for developer or ML products using controlled experiments or benchmark harnesses.
Strong communication skills to collaborate with researchers, engineers, and product teams.

Save