Solutions Architect, AI for Science and HPC

Posted 2 Days Ago
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2 Locations
In-Office or Remote
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
This role involves leveraging Generative AI for scientific applications, leading collaborations, and providing technical guidance to clients on NVIDIA's AI solutions.
Summary Generated by Built In

Generative AI is revolutionizing. Ranging from supercomputing, higher education, manufacturing, semiconductors, energy storage, climate science and agriculture. The advent of AI models and tools such as ClimaX, GenSLM, MatterGen, etc are some exemplars of adapting AI for scientific research and discoveries. We are now looking for a Senior Solution Architect to work with leading science and research institutes in Japan, promoting the adoption of GPU-accelerated computing solutions—including machine learning, deep learning, and especially generative AI for scientific discovery and research.

What you'll be doing:

  • Exploring the latest advancement in GenAI (model training, fine tuning and customization), while supporting building AI for Scientific use cases.

  • Lead research collaboration working closely with internal technical stakeholders, from Headquarters to Worldwide.

  • Enabling NVIDIA strategic customers to build AI solutions using accelerated computing stack including NIMs and NeMo microservices.

  • Collaborate with developers and onboard them to NVIDIA AI platforms and services by providing deep technical guidance.

  • Drive conversations, build architectures and demos to accelerate the customer AI journey based on NVIDIA products, and work closely with our business development and marketing teams.

  • Create or run Proofs of Concept and demos that require presentation skills, the explanation of complex topics, and Python coding to execute data pipelines, train ML/DL models, and deploy them on container-based orchestrators.

What we need to see:

  • BS, MS or PhD in Computer Science, Engineering, Mathematics, or Physics

  • Excellent verbal, written communication, and technical presentation skills in Japanese. Business level English communication is also a requirement.

  • 5+ years of industry or academic experience related to Generative AI or Deep Learning

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

  • Ability to multitask effectively in a dynamic environment, strong analytical and problem-solving skills!

  • Proactive and have a strong desire to share knowledge with clients, partners and co-workers

Ways to stand out from the crowd:

  • Significant technical proficiency in high-performance computing, AI/ML and/or material discovery, climate, bio science and related field.

  • Experience leading technical collaborations with engineering and product teams - including architectural design, code reviews, technical mentorship, and delivery of technical talks or workshops

  • Expertise in deploying large-scale training and inferencing pipeline

  • A deep understanding of the latest generative AI or deep learning methods and algorithms

NVIDIA is widely considered to be one of the technological world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you're creative and autonomous, we want to hear from you!

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

Bash
C/C++
Deep Learning
Generative Ai
Gpu-Accelerated Computing
Linux
Machine Learning
Python
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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