NVIDIA’s Worldwide Field Operations (WWFO) team is looking for a Solution Architect with expertise in Machine Learning (ML), Deep Learning (DL) and Data Science applications to work with our Hyperscalers partners. In our Solutions Architecture team, we work with the most exciting platform for accelerated computing and drive the latest breakthroughs in artificial intelligence. We need individuals who can enable customer and partner productivity. Our goal is to develop lasting relationships with our technology partners, making NVIDIA an integral part of end-user solutions. We are looking for someone always thinking about artificial intelligence, someone who can maintain alignment in a fast paced and constantly evolving field.
You will be working with the latest HPC architectures coupled with the most advanced neural network models, changing the way people interact with technology. As a Solutions Architect, you will be the first line of technical expertise between NVIDIA, our Hyperscaler partners and our end-customers. Your duties will vary from working on proof-of-concept demonstrations, to driving relationships with key technical executives and managers to evangelize accelerated computing and Generative AI. Dynamically engaging with developers, scientific researchers, data scientists, IT managers and senior leaders is a meaningful part of the Solutions Architect role and will give you experience with a range of challenges and solutions.
What You’ll Be Doing:
Develop and demonstrate solutions based on Hyperscalers and NVIDIA’s pioneering GenAI software and hardware technologies to developers
Work directly with key customers and our Hyperscalers partners to understand their challenges and provide the best solutions based on NVIDIA products
Perform in-depth analysis and optimization to ensure the best performance on GPU-accelerated systems using NVIDIA software platform. This includes support in optimization of both training and inference pipelines
Partner with Engineering, Product and Sales teams to understand developer’s challenges and plan for the best suitable solutions. Enable development and growth of product features through customer feedback and proof-of-concept evaluations
Build industry expertise and become a contributor in integrating NVIDIA technology into Enterprise Computing architectures
What We Need to See:
MS/PhD or equivalent in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields
3+ years of academic and/or industry experience in fields related to machine learning, deep learning and/or data science
You are excited to work with multiple levels and teams across organizations (Engineering, Product, Sales and Marketing team)
Excellent ability to listen, both verbal and written communication skills, and being comfortable with presenting technical solutions in English
Expertise in deploying large-scale training and inferencing pipeline on Hyperscaler’s infrastructure
You are a self-starter with interest in growth, passion for continuous learning and sharing findings across the team
Ways to Stand Out from The Crowd:
Experience running and optimizing large scale distributed DL training
Expertise in optimizing inference pipeline, using a range of inferencing technics (e.g., understanding of model compression techniques, model compilation or model serving)
Background with working with larger transformer-based architectures
Experience using DevOps technologies such as Docker, Kubernetes, Singularity, etc.
Understanding of HPC systems: data center design, high speed interconnect InfiniBand, cluster storage and scheduling related design and/or management experience
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