NVIDIA

Solutions Architect, Applied AI

NVIDIA

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Salary

💰 $148,000 - $235,750 per year

Job Level

Mid-LevelSenior

Tech Stack

CloudKerasKubernetesLinuxPythonPyTorchTensorflow

About the role

  • Develop end-to-end AI solutions for enterprise use cases
  • Help customers adopt NVIDIA AI SDKs and APIs and design GPU-accelerated pipelines to optimize compute utilization and performance
  • Build solutions using deep learning technologies: language and multimodal models, information retrieval, domain customization, reinforcement learning, reasoning, inferencing, agentic systems
  • Build reference architectures to deploy and optimize workloads at large scale
  • Improve NVIDIA products through engineering contributions and build creative solutions to scaling challenges
  • Deliver hands-on training and share expert knowledge across the organization and community
  • Act as the face and trusted expert advisor for customers and partners

Requirements

  • BS, MS, or Ph.D. in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar (or equivalent experience)
  • 5+ years experience using deep learning frameworks and libraries such as PyTorch, Tensorflow/Keras, Hugging Face Transformers, Megatron-LM, and DeepSpeed
  • Expertise running deep learning jobs on GPUs using SLURM and Kubernetes
  • 5+ years experience with Python and Linux; demonstrated coding and debugging skills
  • Hands-on experience customizing AI models: distillation, pre-training, supervised finetuning, reinforcement learning, reasoning, evaluation, guard railing, and data curation
  • Demonstrated expertise in accuracy and performance profiling and optimization for AI training and inference workloads
  • Ability to learn fast and adapt to change
  • Clear written and oral communication skills; ability to collaborate with executives and engineering teams
  • (Nice to have) Background with NVIDIA AI Enterprise software (NeMo), experience training foundational models, experience on high-performance NVIDIA GPU computing clusters, extensive engineering and customer collaboration experience
  • (Nice to have) Willingness and ability to dig into unfamiliar territories to solve complex problems