Tech Engagement Lead - Model Builder

at Nvidia
📍 Santa Clara, United States
USD 184,000-287,500 per year
SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Kubernetes @ 3 Distributed Systems @ 7 Leadership @ 6 Networking @ 4 Performance Optimization @ 6 Reporting @ 4 PyTorch @ 3 CUDA @ 4 GPU @ 4

Details

NVIDIA is seeking a highly influential Generative AI Technical Engagement Lead to evangelize, drive, and support the seamless adoption and accelerate the performance of NVIDIA's accelerated computing stack across critical AI model development initiatives with leading AI model builders. As a key technical driver, you will facilitate deep technical integration and deepen collaboration around NVIDIA's hardware, systems, and software libraries within partner core development pipelines. The role operates at the intersection of product vision, advanced technical execution, and high-level customer engagement, influencing model architecture optimization, training infrastructure investments, and ensuring deployment of robust, scalable generative AI solutions.

Responsibilities

  • Lead technical engagement with senior technical leaders and research teams at AI model builders; serve as primary technical point of contact.
  • Optimize partner workflows by leveraging NVIDIA's complete stack for end-to-end generative AI workflows.
  • Accelerate integration of NVIDIA generative AI technologies including GPU architectures, DGX systems, high-performance networking (InfiniBand), CUDA-X libraries, NeMo frameworks, and inference libraries such as TensorRT.
  • Integrate NVIDIA hardware and software into training and inference pipelines of large model builders.
  • Support and strengthen technical implementation plans with partner engineering and research teams; define technical objectives, performance targets, and timelines.
  • Represent software and partner needs to internal NVIDIA product and engineering teams; contribute to product roadmap decisions based on findings from large-scale model training and inference environments.
  • Maintain strategic partner relationships: run regular cadence meetings, document insights, track progress, and provide internal reporting on adoption and impact.
  • Share best practices and standard methodologies for designing and optimizing highly scalable generative AI model development pipelines.
  • Stay current with NVIDIA hardware, libraries, and system updates and proactively share optimizations with partner teams.

Requirements

  • B.S. degree or equivalent experience.
  • 7+ years of experience in technical product or engineering roles, with focus areas including AI/ML, high-performance computing (HPC), or distributed systems.
  • Extensive experience with platforms enabling large-scale AI/ML training and inference workloads, including distributed systems, data infrastructure, and GPU cluster technologies.
  • Hands-on knowledge of large model architectures (e.g., Transformers, Diffusion Models) and familiarity with deep learning frameworks (e.g., PyTorch, JAX).
  • Practical experience with NVIDIA AI acceleration libraries and stacks (CUDA, cuDNN, NCCL, CUDA-X libraries, TensorRT, NeMo).
  • Strong understanding of compute infrastructure: GPU cluster management, high-speed networking (e.g., InfiniBand), parallel file systems, and deployment across on-premise and cloud infrastructures.
  • Experience with distributed training, inference orchestration, and model customization techniques.
  • Familiarity with container orchestration and cloud-native technologies for AI workloads (e.g., Kubernetes).
  • Proven ability to communicate and influence senior engineering and research leadership, translate NVIDIA technology capabilities into business and model development value.
  • Demonstrated success operating in fast-paced environments and driving results in AI research collaborations.

Ways to Stand Out / Preferred

  • Hands-on experience with LLMs, diffusion models, distributed training frameworks, and advanced optimization techniques; ability to prototype and integrate quickly into model pipelines.
  • Experience influencing complex product and research decisions and nurturing high-impact partner relationships.
  • Deep expertise in large-scale system performance optimization and cloud-native architectures for AI.

Benefits and Additional Information

  • The base salary range is 184,000 USD - 287,500 USD. Base salary will be determined based on location, experience, and similar roles.
  • Eligible for equity and NVIDIA benefits (see NVIDIA benefits page).
  • Applications accepted at least until October 9, 2025.
  • NVIDIA is an equal opportunity employer and committed to fostering a diverse work environment.