Senior Solutions Architect, DL Training

NVIDIA • Santa Clara, CA

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About The Position

NVIDIA is seeking an experienced Senior Solutions Architect to help customers build, scale, and optimize AI training solutions using NVIDIA GPU hardware and software on cloud computing platforms. The role focuses on foundation model pre-training and post-training, especially reinforcement learning. As a trusted technical advisor, the architect will engage with developers, researchers, and infrastructure engineers at strategic technology customers and collaborate with NVIDIA business, product, and engineering teams to inform product strategy. The position calls for hands-on technical depth and the ability to translate customer needs into scalable solutions using NVIDIA’s accelerated computing platform.

The architect will work with Cloud Service Providers to design, build, and demonstrate scalable AI training solutions, lead customer engagements from architecture and proofs of concept through production adoption, and develop and optimize end-to-end training workflows. The role also involves building customer-specific proofs of concept, diagnosing performance bottlenecks, supporting platform adoption, and presenting technical recommendations to audiences ranging from engineering teams to executives. Occasional travel is required for on-site customer engagements and industry events. The position is an existing vacancy. Applications will be accepted at least until November 9, 2026. Employees are eligible for equity and benefits.

Requirements

• BS, MS, or PhD in Computer Science, Electrical or Computer Engineering, Statistics, Physics, or a related technical field, or equivalent experience.
• At least 5 years of relevant professional experience in solutions architecture, software engineering, ML engineering, research engineering, or related technical roles, including at least 3 years of hands-on experience with large-scale AI systems or distributed training.
• Strong programming and debugging skills in Python, with hands-on experience developing and optimizing deep learning workloads using PyTorch.
• Practical experience with foundation model pre-training or post-training and a strong understanding of the broader model development lifecycle.
• Demonstrated ownership of an end-to-end training workflow, including data preparation, training configuration, execution, evaluation, and troubleshooting.
• Experience with multi-GPU and multi-node training, including distributed parallelism, mixed precision, memory optimization, and checkpointing.
• Track record of deploying GPU workloads in cloud computing environments such as AWS, GCP, or Azure, with knowledge of containers and workload orchestration.
• Ability to lead technical engagements, solve complex problems, and communicate technical ideas and tradeoffs clearly to technical and non-technical audiences.

Nice To Haves

• Hands-on experience spanning pre-training and post-training of large language or multimodal models, including supervised fine-tuning and reinforcement learning.
• Experience with reinforcement learning from human feedback or verifiable rewards, including reward design, rollout generation, policy optimization, and training stability.
• Experience with NVIDIA NeMo Framework, Megatron Core, Megatron Bridge, PyTorch FSDP, DeepSpeed, or comparable distributed training technologies.
• System-level understanding of GPU platforms and experience profiling and optimizing training workloads, with measured improvements in throughput, scaling efficiency, reliability, or cost.

Responsibilities

• Work with Cloud Service Providers to design, build, and demonstrate scalable AI training solutions using NVIDIA hardware and software.
• Lead technical engagements across foundation model pre-training and post-training, guiding customers from architecture and proofs of concept to production adoption.
• Develop and optimize end-to-end training workflows involving data preparation, distributed training, checkpointing, evaluation, and reinforcement learning pipelines.
• Build customer-specific proofs of concept that address technical and business needs and demonstrate improvements in training performance, reliability, and efficiency.
• Help customers diagnose and resolve bottlenecks involving GPU compute, memory, communication, networking, storage, and workload orchestration.
• Partner with Sales Account Managers and Developer Relations Managers to identify opportunities and drive adoption of NVIDIA AI training platforms.
• Prepare and deliver technical presentations, workshops, and architecture reviews for researchers, engineers, technical leaders, and executives.
• Establish close technical relationships with customers, lead roadmap and architecture discussions, and collaborate with NVIDIA engineering and product teams to resolve issues and inform future capabilities.

Benefits

• Equity
• Benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Senior