NVIDIA
Developer Relations Manager, Energy Startups
$152K–$242K
US, CA, Santa Clara +1 · Manager · Full-time · Posted Jul 10, 2026
- Location
- US, CA, Santa Clara
US, Remote - Experience
- 5+ years overall in the technology industry, including 3+ years of hands-on AI development in the energy sector using NVIDIA technologies.
- Education
- Bachelor's or Master's degree or equivalent experience in Computer Science, Engineering, or a related field (or equivalent experience).
About the job
Leads technical engagement with energy-sector developers, startups, and ISVs to drive adoption of NVIDIA AI and computing technologies in partner products and energy applications.
What you'll do
- Advise energy developers and partners; provide reference implementations, sample code, demos, onboarding, and integration support.
- Integrate NVIDIA software into partner products and pipelines, resolve architectural challenges, and promote ecosystem adoption.
- Identify ecosystem opportunities and share field insights with engineering, product, and partner teams to influence roadmaps and adoption strategies.
What they ask for
- Bachelor's or Master's degree or equivalent experience in Computer Science, Engineering, or a related field.
- 5+ years of overall professional experience in the technology industry, including 3+ years of hands-on AI development in the energy sector using NVIDIA technologies.
- Experience supporting developer programs, technical ecosystems, or energy-sector ISVs, with a track record growing developer initiatives with prominent tech and energy startups and ISV partners.
- Proficiency in AI/ML development, CUDA-X libraries, and large-scale training/inference frameworks; strong technical collaboration, project management, and communication skills.
Nice to have
- Hands-on optimization of energy-sector applications across oil, gas, nuclear, and renewables.
- Experience with GPU-accelerated energy systems such as seismic imaging, grid optimization, simulations, or energy forecasting.
Pay
152,000 USD - 241,500 USD (base salary)
Tools
NVIDIA technologies, CUDA-X libraries, AI/ML, large-scale training/inference frameworks, NVIDIA software stack, SDKs, NIMs
AI focus
Supports adoption and integration of AI and accelerated computing for energy-sector applications, including exploration, grid optimization, reservoir simulation, predictive maintenance, seismic processing, energy modeling, and monitoring.
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