At NVIDIA, we’re solving the world’s most challenging problems with our unique approach to accelerated computing. We’re looking for passionate technologists with software and hardware. In this Solutions Architect role, you will help researchers and developers accelerating their key workloads by using NVIDIA platform. You'll define and deliver strategic partnerships, lead fruitful technical collaborations, provide first-line technical expertise and developer support, and guide NVIDIA's product strategy.
If you are passionate about AI and how it can be applied to address real-world problems, we should talk. NVIDIA is the world leader in GPU accelerated computing and AI and is looking for developers like you to design and build enterprise AI solutions using our newest technology. As a member of the Solution Architect team, you will work closely with customers and partners to solve hard problems in customizing and deploying AI workloads at scale.
What you'll be doing:
Create fruitful technical engagements with AI development teams in frontier model makers in Korea and lead strategic relationships with top developers and influential researchers.
Help them develop AI models more efficiently by proposing state-of-the-art training and optimization frameworks including Megatron-LM, Megatron-Bridge, NeMo-RL, NeMo-Gym, TensorRT Model Optimizer, and TensorRT-LLM.
Promote the results of the collaboration between NVIDIA and those teams with the support of marketing teams by publishing press releases and celebrate together by presenting them at GTC.
Continuously keep up with the latest AI training and optimization technologies that not only NVIDIA but also the community researchers provide to the market.
What We Need To See:
5+ years of hands-on experience in full AI model lifecycle, including pre-training, supervised fine-tuning, post-training such as reinforcement learning, optimization, and evaluation.
Strong software engineering skills, including debugging, performance analysis, and test development.
World-class communication skills with a demonstrated ability to articulate a value proposition to technical and non-technical audiences.
MS/PhD in Computer Science or Engineering or equivalent experience.
Ways To Stand Out From The Crowd:
Excellent English communication skills
Understanding of infrastructure factors that can affect AI model development such as GPU architecture, server block diagram, or networking bandwidth among GPU servers or between GPU servers and shared storage.
We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, we want to hear from you.
Skills Required
- 5+ years of hands-on experience in full AI model lifecycle
- Strong software engineering skills, including debugging, performance analysis, and test development
- MS/PhD in Computer Science or Engineering or equivalent experience
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
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.”
