Solutions Architect, Generative AI Specialist
Do you want to be part of the team that brings Artificial Intelligence (AI) emerging technology to the field? We are looking for a Solution Architect or Data Scientist to join the NVIDIA AI Specialist team focused on Machine Learning, Deep Learning, and Accelerated Data Analytics.
If you are passionate about 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 AI Specialist Solution Architecture team, you will work closely with customers and partners to tackle hard problems across industries and build and deploy AI solutions in production at scale.
What you’ll be doing:
A big part of our day-to-day job is developing end-to-end Machine Learning & Deep Learning solutions and recipes that enable Enterprise use cases. We work with customers to successfully adopt NVIDIA AI SDKs and APIs by providing deep technical product expertise.
We solve customer problems by creating solutions using our innovative technology for Machine Learning and Deep Learning including Large Language Models, Computer Vision systems, Recommender systems, and Advanced Generative AI systems.
As we work with customers across multiple industries, we identify common trends that lead to success. With this knowledge, we help improve NVIDIA products and build creative solutions to overcome adoption challenges.
We contribute to the wider organization and community by sharing our expert knowledge with others. This can vary from building hands-on training to writing papers, developer blogs, and teaching.
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 analytical and problem-solving skills.
Strong coding development and debugging skills. Including experience with Python, C/C++, Bash, as well as Cloud services, Spark and Linux.
Experience working with NVIDIA Infrastructure, DevOps and MLOps including but not limited to Docker/Containers, Kubernetes, and Data Center or Cloud AI deployments.
Ability to multitask effectively in a dynamic environment.
Clear written and oral communications skills with the ability to effectively collaborate with executives and engineering teams.
Successful candidates will be able to demonstrate a strong desire to share knowledge with clients, partners, and co-workers.
Ways to stand out from the crowd:
Demonstrate expertise and hands-on experience with NVIDIA AI products. Some products of interest include Machine Learning (RAPIDS and sparks-rapids), Natural Language Processing and Large Language Models (NVIDIA NEMO), Logistics and Route Optimization (NVIDIA CuOpt), Recommender systems (NVIDIA Merlin) and Generative AI technologies (AI Foundations).
Software development experience in enterprise scale applications and experience in complete Software Development Life Cycle (SDLC).
Experience and understanding of the latest Deep Learning Architectures and training techniques. Most importantly, Transformers Models and the latest customization techniques such as SFT, Parameter Efficient Fine Tuning, and Reinforcement Learning Human Feedback.
Leadership experience working with customers and managing large projects with multiple collaborators.
Show willingness and ability to dig into unfamiliar territories to solve complex problems relying on experience from previous work.