Company: NVIDIA
Industry:- Private
Employment Type:- Full-time
Work Hours:- 8 Hours
Locations:- USA
Full Job Description:
NVIDIA is looking for a Solutions Architect or Data Scientist to work with our largest global alliance partners to enable them with our portfolio of GPU Accelerated Computing solutions i.e. Machine Learning and Deep Learning, specifically Generative AI and to build comprehensive multi-cloud, hybrid, and on-prem solutions.
We need a passionate, hard-working, and creative individual who has the skills and aim to work in a fast-evolving technological environment that is always on the cutting edge of AI and Accelerated Computing. This individual is self-driven, excellent in communication and partnership, stays on top of tasks, mission-focused, and outcome-oriented. Duties will include being a technical data science and accelerated computing platform advisor to our largest global alliance partners. This includes architecting and creating prototypes, building, pre-training, fine-tuning and p-tuning LLMs, and finding the best deployment scenarios for customers.
What you’ll be doing:
- 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 deploying on container-based orchestrators.
- A considerable part of the day-to-day job is keeping up to date on the state of the art in the production Deep Learning and Machine Learning ecosystem. You’ll be called on to help architect and scale high-performance, distributed AI deployments that are built on the latest NVIDIA GPU supercomputers.
- Document what you know, and guide others. This can vary from building targeted training for partners and other Solutions Architects to writing whitepapers, blogs, and wiki articles, to working through challenging problems with a partner on a whiteboard.
- Answer questions and provide mentorship. Work with Partner Business Managers to assist partners and customers on their mission-critical projects. You will help them build their GPU-enabled Accelerated Compute data centers and get the most out of their investment.
- We make heavy use of conferencing tools, but some travel is required for this role. You are empowered to find the best way to get your job done and do what it takes to make our partners successful.
Above all, you will be the person that our alliance partners call on when they need to get technical in crafting AI solutions for customers using NVIDIA technology. Backed up by the other Solution Architects, NVIDIA Engineering, and the whole of NVIDIA, you’ll get to be the face and brains of NVIDIA that our partners will be relying on.
What we need to see:
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- 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 data center design including computing, 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.
- Have a strong desire to share knowledge with clients, partners, and co-workers.
Ways to stand out from the crowd:
- 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, Infinibadand, and other networking technologies and Operating systems
- Have a willingness and ability to dig into unfamiliar territories to tackle complex problems and be a great listener.
