NVIDIA · 5 hours ago
Tech Engagement Lead - Model Builder
California, United States
Full-time
Onsite
Senior Level
$184K/yr - $288K/yr
7+ years expNVIDIA is seeking a highly influential Generative AI Technical Engagement Lead to evangelize for, drive, and support the seamless adoption of NVIDIA's accelerated computing stack. The role involves engaging with AI model builders, driving technical integration, and influencing product roadmaps to enhance the performance of generative AI solutions.
Artificial Intelligence (AI)Consumer ElectronicsGPUHardwareSoftwareVirtual Reality
Hiring Manager
Dayna W.
Responsibilities
Lead Technical Engagement: Engage with senior technical leaders and research teams at AI model builders. Optimize their workflows by leveraging NVIDIA's complete stack for their end-to-end generative AI workflows. Serve as a primary technical point of contact
Drive Integration: Accelerate the technical integration of NVIDIA's core generative AI technologies. This includes NVIDIA GPU architectures, DGX systems, high-performance networking (InfiniBand), CUDA-X libraries, NeMo frameworks, and inference libraries like TensorRT. Integrate these into the training and inference pipelines of large model builders
Strengthen Partnerships: Support and strengthen technical implementation plans with partner AI engineering and researchers. Define clear technical objectives, performance breakthroughs, and timelines. Align these with their long-term model development goals and NVIDIA's AI strategy
Influence Product Roadmaps: Represent the software needs of large model builders to internal NVIDIA product and engineering teams. Contribute to product roadmap decisions by synthesizing findings from large-scale model training and inference environments. Identify cross-industry patterns and advocate for improvements to NVIDIA's core technologies
Maintain Strategic Relationships: Conduct regular cadence meetings. Document insights, track progress, and provide consistent internal reporting on the adoption and impact of NVIDIA technologies
Showcase Best Practices: Share standard methodologies for crafting and optimizing highly scalable generative AI model development pipelines across all stages. Focus on the context of large model development
Stay Updated: Keep current with the latest NVIDIA hardware, libraries, and system updates. Proactively share relevant insights and optimizations with partner model development teams
Qualification
Required
B.S. degree or equivalent experience
7+ years of experience in technical product or engineering roles. Focus areas include AI/ML, high-performance computing, or distributed systems. Emphasis on core technology integration and partner collaborations is key
Extensive experience working with or developing platforms that facilitate large-scale AI/ML training and inference workloads. This includes distributed systems, data infrastructure, and groundbreaking GPU cluster technologies
Hands-on knowledge of large model architectures (e.g., Transformers, Diffusion Models). Familiarity with core deep learning frameworks (e.g., PyTorch, JAX), and NVIDIA AI acceleration libraries (e.g., CUDA, cuDNN, NCCL, TensorRT, NeMo). Understand techniques for model customization, distributed training, and inference orchestration
Strong understanding of compute infrastructure environments. This includes GPU cluster management, high-speed networking, parallel file systems, and deployment across on-premise and cloud infrastructures. Possess specific understanding of how large model builders operate at scale
Proven ability to communicate and influence senior leadership across engineering and research leaders at partner organizations. Link NVIDIA technology capabilities to crucial AI model development and business value
Successfully navigated fast-paced environments, taking decisive action to achieve results. Especially valuable in AI research collaborations
Skilled at connecting with engineers, researchers, executives, and multi-functional teams
Preferred
Hands-on experience with large language models (LLMs), diffusion models, distributed training frameworks, and advanced optimization techniques. Ability to prototype quickly and integrate into model development pipelines
Influence complex product and research decisions by nurturing positive relationships and understanding model builder needs
Eager drive, strategic curiosity. Anticipate market trends in AI, shape NVIDIA's roadmap, and champion innovation. Understand the large model builder landscape
Act as a technical advocate for NVIDIA GPU systems and software stack within assigned large model builder partners. Showcase its technical capabilities and strong value proposition
Understanding of large-scale system performance optimization, container orchestration (e.g., Kubernetes), and Cloud Native technologies for AI workloads
Benefits
Equity
Benefits
Company
NVIDIA
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.
10001+ employees
H1B Sponsorship
NVIDIA has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (1418)
2024 (1356)
2023 (976)
2022 (835)
2021 (601)
2020 (529)
Funding
Current Stage
Public CompanyTotal Funding
$4.09BKey Investors
ARPA-EARK Investment ManagementSoftBank Vision Fund
2023-05-09Grant· $5M
2022-08-09Post Ipo Equity· $65M
2021-02-18Post Ipo Equity
Leadership Team
Jensen Huang
Founder and CEO
Michael Kagan
Chief Technology Officer
Recent News
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