Senior Solutions Architect, DL Training

Responsibilities: Design, build, and demonstrate scalable AI training solutions with NVIDIA tech for cloud providers Lead technical engagements across foundation model pre-training and post-training Develop end-to-end training workflows including data prep, distributed training, checkpointing, and evaluation (RL pipelines) Create customer-specific proofs of concept addressing critical technical and business needs Identify and resolve bottlenecks across GPU compute, memory, networking, storage, and orchestration Collaborate with Sales and Developer Relations to drive NVIDIA platform adoption Prepare and deliver technical presentations, workshops, and architecture reviews Engage with customers to shape roadmaps and inform product capabilities

Key requirements: BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Statistics, Physics, or related field, or equivalent experience 5+ years in solutions architecture, software ML engineering, or related roles 3+ years hands-on with large-scale AI systems or distributed training Strong Python and debugging skills; hands-on experience with PyTorch Experience with foundation model pre-training/post-training and model development lifecycle End-to-end training workflow ownership (data prep, config, execution, evaluation, troubleshooting) Experience with multi-GPU/multi-node training, distributed parallelism, mixed precision, memory optimization, checkpointing Deploying GPU workloads in cloud (AWS/GCP/Azure) with containers and orchestration Ability to lead technical engagements and communicate complex ideas to technical and non-technical audiences strong communication skills leadership and stakeholder management problem-solving and ownership Python PyTorch distributed training