Posted:
9/2/2024, 6:50:35 AM
Location(s):
Shanghai, China ⋅ Beijing, China
Experience Level(s):
Senior
Field(s):
AI & Machine Learning ⋅ Software Engineering
NVIDIA’s Solution Architecture team is looking for a AI-focused Solution Architect with expertise in Large Language Model, generative AI, or recommender system. We work with the most exciting computing hardware and software, driving the latest breakthroughs in artificial intelligence. We need individuals who can enable customer productivity and 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 constructive collaboration in a fast paced, rapidly evolving field, someone able to coordinate efforts between corporate marketing, industry business development and engineering. You will be working with the latest HPC architecture 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 and our customers. Your duties will vary from working on proof-of-concept demonstrations, to driving relationships with key executives and managers to evangelize accelerated computing. 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 partners and concerns.
What you’ll be doing:
Assisting field business development in guiding the customer build/extend their GPU infrastructures for AI.
Help customers build their large-scale projects, especially Large Language Model (LLM) projects.
Engage with customers to perform in-depth analysis and optimization to ensure the best performance on GPU architecture systems. This includes support in optimization of both training and inference pipelines.
Partner with Engineering, Product and Sales teams to develop, plan best suitable solutions for customers. 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 or PhD in Electrical Engineering, Computer Science/Engineering, Mathematics, Physics, or a related field (or equivalent experience).
3+ years of work-related experience in AI for natural language processing (NLP) and large language model (LLM).
Knowledge of application areas such as natural language processing and computer vision.
Excellent programming skills in some rapid prototyping environments such as Python, C++ and parallel programming (e.g., CUDA) is a plus.
Expertise with deep learning frameworks such as PyTorch.
Strong written and oral communications skills in English.
Ways to stand out from the crowd:
Background in large language model, generative AI, recommender system.
Demonstrated experience optimization workloads with GPU technology.
Experience with NVIDIA AI and Data Science software and platform.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and talented people in the world working for us. If you are creative and autonomous, we want to hear from you!
NVIDIA is committed to encouraging 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.
Website: https://www.nvidia.com/
Headquarter Location: Santa Clara, California, United States
Employee Count: 10001+
Year Founded: 1993
IPO Status: Public
Last Funding Type: Grant
Industries: Artificial Intelligence (AI) ⋅ GPU ⋅ Hardware ⋅ Software ⋅ Virtual Reality