Solutions Architect, Generative AI

Do you want to be part of the team that brings Artificial Intelligence (AI) technology to the field? We are looking for a Solution Architect or Data Scientist to join the NVIDIA AI Enterprise (NVAIE) SA Segment team. We specialize on the newest technology and advances in Machine Learning, Deep Learning, Generative AI, and Cloud. The vision of the NVAIE Segment team is to use our deep expertise to guide and enable the successful adoption at data center scale of NVIDIA AI Enterprise Software!

If you are passionate about Generative AI and how it can be applied to solve real-world problems, we should talk. NVIDIA is the world leader in GPU accelerated computing and AI, and is looking for developers like you to design and build enterprise AI solutions using our newest technology. As a member of the NVAIE Segment Solution Architecture team, you will work closely with customers and partners to tackle hard problems in customizing and deploying Generative AI workloads in production at scale.

What you’ll be doing:

• A huge part of our work involves developing end-to-end Generative AI solutions for enterprise use cases. We help customers adopt NVIDIA AI SDKs and APIs by offering deep technical expertise and designing GPU-accelerated pipelines that optimize compute resource utilization and improve workload performance.

• We solve customer problems by building solutions using Machine Learning and Deep Learning technology including language and multimodal models, information retrieval, domain customization, reasoning, inferencing, agentic systems, and other sophisticated Generative AI workloads.

• As we work with customers across multiple industries, we build the reference architectures needed to deploy and optimize workloads at large scale. With this knowledge, we help improve NVIDIA products and build creative solutions to overcome scaling challenges.

• We contribute to the wider organization and community by sharing our expert knowledge with others. This can vary from product engineering contributions to building and delivering hands-on training.

Above all, you will be part of the team that helps bring NVIDIA technology to life in the Enterprise! We empower you and give you the tools to achieve this with the backing of all of NVIDIA, including other Solution Architects, Product, Engineering and Research teams. You’ll get to be the face and trusted expert advisor that our customers and partners rely on.

What we need to see:

• Strong foundational expertise, from a BS, MS, or Ph.D. degree in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar (or equivalent experience).

• 5+ years experience demonstrating an established track record in Deep Learning and Machine Learning; experience with GPUs as well as expertise in using deep learning frameworks such as TensorFlow or PyTorch.

• Strong coding development and debugging skills. Including experience with Python, C/C++, Bash, and Linux.

• Real-world development of large scale Gen AI applications, including but not limited to information retrieval, model pre-training and post-training, model and pipeline evaluation, inference optimization, guard-railing, agents, and reasoning systems.

• Demonstrated experience with cluster orchestration tools including Docker, Kubernetes, and SLURM across cloud service providers and on premise.

• Demonstrated expertise in optimizing AI training and inference workloads over high-performance networks, including both Ethernet and InfiniBand fabrics.

• Ability to learn fast and quickly adapt to change.

• Clear written and oral communications skills with the ability to effectively collaborate with executives and engineering teams.

Ways to stand out from the crowd:

• Proven expertise and hands-on experience with NVIDIA AI products including NIM, Nemo Retriever, Nemo Microservices, and Nemo Framework.

• Expertise on NVIDIA Spectrum-X.

• Experience with NVIDIA Collective Communication Library (NCCL).

• Extensive engineering and customer experience on projects with multiple collaborators.

• Show willingness and ability to dig into unfamiliar territories to solve complex problems relying on experience from previous work.