Deep Learning Solutions Architect
24 hours ago
NVIDIA is seeking a highly skilled Solutions Architect to join our team and work with our largest global alliance partners to enable them with our portfolio of GPU Accelerated Computing solutions, including Machine Learning and Deep Learning. As a Solutions Architect, you will be responsible for architecting and creating prototypes, building, pre-training, fine-tuning, and p-tuning LLMs, and finding the best deployment scenarios for customers.
Key Responsibilities- Creating or running Proof of Concept and Demos that require presentation skills, explanation of complex topics, writing Python code to execute data pipelines and train ML/DL models, and deploy on container-based orchestrators.
- Keeping up to date on the state of the art in the production Deep Learning and Machine Learning ecosystem and helping to architect and scale high-performance, distributed AI deployments built on the latest NVIDIA GPU supercomputers.
- Documenting knowledge and guiding others through building targeted training for partners and other Solutions Architects, writing whitepapers, blogs, and wiki articles, and working through challenging problems with a partner on a whiteboard.
- Answering questions and providing mentorship, working with Partner Business Managers to assist partners and customers on their mission-critical projects, and helping them build their GPU-enabled Accelerated Compute datacenters and get the most out of their investment.
- Using conferencing tools and some travel is required for this role, and you are empowered to find the best way to get your job done and do what it takes to make our partners successful.
- BS or MS in Engineering, Mathematics, Physics, or Computer Science (or equivalent experience).
- 5+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow or PyTorch, GPU and CUDA experience extremely helpful.
- Experience working with DevOps, including but not limited to Docker/Containers, Kubernetes, and Data Center deployments.
- Deep understanding of dense datacenter design including compute, storage, and networking.
- Ability to multitask effectively in a dynamic environment.
- Strong analytical and problem-solving skills.
- Clear written and oral communication skills with the ability to effectively collaborate with management and engineering.
- Strong desire to share knowledge with clients, partners, and co-workers.
- Extensive knowledge and hands-on experience with recent advancements in LLMs and GenAI.
- Experience developing with ML/DL frameworks and MLOps ecosystem of partners and solutions in the cloud and on-prem.
- Background with cloud-based solution designing, APIs, and Microservices, orchestration platforms, storage solutions, and data migration techniques.
- Experience or good knowledge of server architectures, PCIe topologies, Infiniband, and other networking technologies and Operating systems.
- Willingness and ability to dig into unfamiliar territories to tackle complex problems and be a great listener.
NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking individuals in the world working for us. If you're creative and autonomous, we want to hear from you.
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