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Developer Relations Manager - Artificial Intelligence

NVIDIA Corporation

Remote - UKRemotePosted Nov 19, 2025
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We are looking for a Developer Relations Manager - Artificial Intelligence passionate about developing modern Artificial Intelligence, and Generative AI applications with a leading CSP. Focus will be on Deep learning, which is making a major impact across research and industry. This Developer Relations Manager will lead our partnerships with developers, within a large partner, and work with engineering, research, applications, and new initiatives. We need creative people who want to build a career at the intersection of AI, machine learning, deep learning, and data analytics. Development Relations Manager should be passionate about innovation, building and driving engineering partnership and strategies to integrate NVIDIA technologies throughout the applications. This position will be a combination of developer advocacy, product management and business development. You and the CSP team are responsible for leading engineering integration and go-to-market activities with a multi-functional team of engineers, product, and marketing partners. You will work closely with many groups within NVIDIA, including Solutions Architects, Software Developers, HW & SW Architecture, and our product and marketing teams. In this role, you can expect high visibility with NVIDIA senior leaders, given the strategic priority for developing computing platform for deep learning and AI. What You'll Be Doing • Lead and develop NVIDIA developer strategy with multi-functional team: Product, Engineering, Applied Research, Marketing, and Sales. • Develop a detailed understanding and prioritization list of services and applications that could benefit from GPU acceleration in the AI / Gen AI space. Lead strategic relationship with key influential researchers, leading product teams, leading developers focused new initiatives. • Establish strategic relationships with Partner/CSP engineering leads & developers, dedicate yourself to making them successful. Turn features requests into actionable engineering and product steering. • Understand application workflow and architectural requirements to enable GPU based workloads acceleration. Integrate NVIDIA GPU acceleration into CSP Applications. Be alert to the competitive landscape and communicate internally. • Create strategic partnership and build community by attending research conferences and hosting technical meetups. Host developers summits; AI, Deep Learning, HPC, Professional Visualization. Engage industry events to speak, collect requirements, establish relationships, showcase NVIDIA GPU accelerated solutions. What We Need To See • BS/MS/PhD in Computer Science or Engineering or equivalent experience. • 15+ years experience with Cloud, AI, Scalable Applications, Data Analytics, and GPU technology. • Good technical understanding of Generative AI, high-performance computing, database analytics. • Solid understanding of machine learning, deep learning, artificial intelligence platforms and ecosystems. • Comfortably work across all major internal functional areas (engineering, sales, marketing, executives), as well as external partners, customers, and content developers. Ways To Stand Out From The Crowd • Demonstrated excellent interpersonal skills (both verbal and written) and evidence of your ability to represent NVIDIA externally. • Excellent social, planning and prioritization skills. • You are a self-starter with approach for growth and passion for continuous learning. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and dedicated people in the world working for us. If you're creative and autonomous, we want to hear from you!

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Original posting: jobs.nvidia.com

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RISC-V ecosystem

NVIDIA Corporation in the RISC-V ecosystem

RISC-V International: Premier Board

Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.

  • NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
  • Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
  • Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage

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