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Solutions Architect, AI Models

NVIDIA· Architect, Solutions
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Santa Clara, CA$152k - $241.5kfull-timePosted 7mo ago

About the role

Solutions Architect to join NVIDIA's AI Software Segment SA team, focusing on enterprise AI solutions using NVIDIA AI models and libraries across the AI model lifecycle, collaborating with customers and partners to deploy AI workloads at scale.

Responsibilities

  • Develop end-to-end AI solutions for enterprise use cases and help customers adopt NVIDIA AI models and libraries with deep technical expertise
  • Tackle AI challenges across the model lifecycle—from data processing and orchestration to training, post-training, reinforcement learning, evaluation, and model optimization
  • Support a broad model portfolio spanning LLMs, multimodal, retrieval, speech, content safety, and edge use cases
  • Partner with enterprise customers in co-design engagements—understanding their data, evaluation criteria, and success metrics to deliver customized AI solutions
  • Improve NVIDIA products and build creative solutions to scaling challenges at the intersection of computer architecture, models, libraries, and AI applications
  • Contribute to the wider organization and community by sharing expert knowledge (open-source projects, product engineering, publishing findings, hands-on training)
  • Be the face and trusted expert advisor to customers and partners, enabling NVIDIA technology in the Enterprise with support from NVIDIA teams

Qualifications

  • BS, MS, or Ph.D. in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar (or equivalent experience)
  • 5+ years of experience with AI frameworks such as PyTorch, JAX, or TensorFlow, and libraries like Hugging Face Transformers
  • Proficiency in Python, software design, debugging, and performance analysis, with 5+ years of Linux experience
  • Hands-on experience with AI model lifecycle (evaluation, failure analysis, pre-training, post-training, RL, model optimization)
  • Expertise in distributed computing methodologies (model and data parallelism)
  • Experience with distributed computing tools like SLURM and Kubernetes for training/evaluating large models on GPUs
  • Ability to learn quickly and adapt to change
  • Clear written and oral communication skills for collaboration with executives and engineering teams

Skills

Required:AI frameworks (PyTorch, JAX, TensorFlow)PythonLinuxModel lifecycleDistributed computing

Benefits

  • Equity
  • Benefits (see NVIDIA benefits page)
Last updated Aug 28, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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