# Senior Solutions Architect

**Company**: NVIDIA
**Location**: Seattle, WA
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-WA-Seattle/Senior-Solutions-Architect--DL-Training_JR2028701?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_8bfe8bdb-060

## Description

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.

As part of the Solutions Architecture team, you will work with cutting-edge computing hardware and software technologies, including large-scale AI training. A Solutions Architect serves as a trusted technical advisor between NVIDIA and customers, engaging with developers, researchers, and infrastructure engineers at strategic technology customers.

**Responsibilities:**

- Design, build, and demonstrate scalable AI training solutions using NVIDIA hardware and software with Cloud Service Providers.

- Lead technical engagements across foundation model pre-training and post-training, assisting customers in moving from architecture and proofs of concept to production adoption.

- Develop and optimize end-to-end training workflows spanning data preparation, distributed training, checkpointing, and evaluation, including reinforcement learning pipelines.

- Build customer-specific proofs of concept addressing critical technical and business needs, demonstrating improvements in training performance, reliability, and efficiency.

- Help customers diagnose and resolve bottlenecks across 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 platforms for AI training.

- Prepare and deliver technical presentations, workshops, and architecture reviews for various audiences.

- Establish close technical relationships with customers, lead roadmap and architecture discussions, and collaborate with NVIDIA engineering and product teams.

**Requirements:**

- BS, MS, or PhD in Computer Science, Electrical or Computer Engineering, Statistics, Physics, or a related technical field, or equivalent experience.

- 5+ years of relevant professional experience in solutions architecture, software engineering, ML engineering, research engineering, or related technical roles, including 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.

- Established 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 Have:**

- Hands-on experience spanning both 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.

You will also be eligible for equity and benefits.

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## Skills

### Required
- Python
- PyTorch
- large-scale AI systems
- distributed training
- GPU computing
- cloud computing

### Nice to have
- reinforcement learning
- NVIDIA NeMo Framework
- Megatron Core
- Megatron Bridge
- PyTorch FSDP
- DeepSpeed

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/US-WA-Seattle/Senior-Solutions-Architect--DL-Training_JR2028701?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)