NVIDIA are seeking dynamic Solution Architects with specialized expertise in training Large Language Models (LLMs), implementing RAG workflows, and agentic inference. You will leverage the full NVIDIA software & hardware ecosystem to design, optimize, and deliver production-grade generative AI solutions for enterprise customers. With competitive salaries and a generous benefits package, we are widely considered to be one of the world’s most desirable employers! We have some of the most forward-thinking and hardworking people in the world working for us and, due to outstanding growth, our best-in-class 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.
What You Will Be Doing:
Architect end-to-end solutions focused on LLM pretraining, fine-tuning, high-performance inference, RAG workflows, and agentic inference orchestration using NVIDIA’s hardware and software platforms.
Collaborate with customers to understand their LLM-related business challenges and design tailored solutions aligned with the NVIDIA ecosystem.
Lead LLM training, distributed optimization, and performance tuning to achieve optimal throughput, latency, and memory efficiency.
Design and integrate RAG workflows and agentic inference pipelines into customer systems; provide technical guidance on best practices.
Collaborate with NVIDIA engineering teams to provide feedback and support pre-sales technical activities (workshops, demos).
What We Need to See:
Master’s / Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience.
4+ years hands-on experience in AI, focusing on open-source LLM training, fine-tuning, and production inference optimization.
Deep understanding of mainstream LLM architectures and proficiency in LLM customization via PyTorch, Hugging Face Transformers.
Solid knowledge of GPU computing, cluster architecture, and distributed parallel training/inference for LLMs.
Competency in agentic inference design and using AI agents to solve business challenges.
Strong communication skills, able to articulate complex technical concepts to technical and non-technical stakeholders.
Ways to Stand Out from the Crowd:
Hands-on experience with NVIDIA’s generative AI ecosystem (TRT-LLM, Megatron-LM, NVIDIA NeMo).
Advanced skills in LLM optimization (quantization, KV Cache tuning, memory footprint reduction).
Experience with Docker, Kubernetes for containerized LLM and agent workflow deployment on-prem.
In-depth knowledge of multi-GPU parallelism and large-scale GPU cluster management.
Skills Required
- Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience
- 4+ years of hands-on AI experience focused on open-source LLM training, fine-tuning, and production inference optimization
- Deep understanding of mainstream LLM architectures
- Proficiency in LLM customization using PyTorch and Hugging Face Transformers
- Knowledge of GPU computing, cluster architecture, and distributed parallel LLM training and inference
- Competency in agentic inference design and applying AI agents to business challenges
- Strong communication skills with technical and non-technical stakeholders
- Hands-on experience with NVIDIA's generative AI ecosystem, including TRT-LLM, Megatron-LM, or NVIDIA NeMo
- Advanced LLM optimization skills, including quantization, KV Cache tuning, and memory footprint reduction
- Experience with Docker and Kubernetes for on-premises containerized LLM and agent workflow deployment
- In-depth knowledge of multi-GPU parallelism and large-scale GPU cluster management
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.”
