NVIDIASolutions Architect, Pre-training and Post-training
NVIDIA is hiring a Solutions Architect, Pre-training and Post-training in Seoul, South Korea. Level rates it ; you can apply on Level.
AI in this role
Provide technical expertise and solutions architecture for AI model pre-training, fine-tuning, and optimization using NVIDIA platforms.
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.
How we rate this
Solutions Architect, Pre-training and Post-training at NVIDIA rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Tell me about a project where deep learning was part of your work. What did you do?
- Tell me about a project where ai model training was part of your work. What did you do?
- Tell me about a project where reinforcement learning was part of your work. What did you do?
- Tell me about a project where optimization was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Fine-tuning, Deep learning, AI Model Training, Reinforcement learning, and Optimization. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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