Job description

Do you want to be part of the team that brings innovative Artificial Intelligence (AI) from research to reality? We are looking for a Solutions Architect to join the AI Software Segment SA team. We specialize in the newest technology and advances in deep learning, Generative AI, and Cloud. The vision of the AI SW Segment team is to use our deep expertise, at the intersection of research and engineering, to guide and enable the successful adoption of NVIDIA AI software in the enterprise! 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 Architecture 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: • A huge part of our work involves developing end-to-end AI solutions for enterprise use cases. We help customers adopt NVIDIA AI models and libraries by offering deep technical expertise. • Tackle sophisticated AI challenges by applying skills across the AI model lifecycle—from data processing and orchestration to training, post-training, reinforcement learning (RL), evaluation, and model optimization. • Support a broad model portfolio spanning LLMs, multimodal, retrieval, speech, content safety, and edge use cases. • Partner with enterprise customers in co-design engagements — understanding their data, evaluation criteria, and success metrics to deliver customized AI solutions. • As we work with customers across multiple industries, we help improve NVIDIA products and build creative solutions to overcome scaling challenges at the intersection of computer architecture, models, libraries, and AI applications. • Contribute to the wider organization and community by sharing your expert knowledge. This can vary from contributing to open-source projects and product engineering to publishing findings and delivering hands-on training. Above all, you will be part of the team that helps bring NVIDIA technology to life in the Enterprise! We empower you and give you the tools to achieve this with the backing of all of NVIDIA, including other Solution Architects, Product, Engineering and Research teams. You’ll get to be the face and trusted expert advisor that our customers and partners rely on. What we need to see: • Strong foundational expertise, from a BS, MS, or Ph.D. degree in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar (or equivalent experience). • 5+ years of experience with AI frameworks such as PyTorch, JAX, or TensorFlow, and libraries like Hugging Face Transformers. • Proficiency in Python programming, software design, debugging, and performance analysis, with at least 5+ years of experience in a Linux environment. • Hands-on experience with AI model lifecycle, including evaluation, failure analysis, pre-training, post-training, RL, and model optimization. • Expertise in distributed computing methodologies, including model and data parallelism. • Experience with distributed computing tools, like SLURM and Kubernetes, for training and evaluating large models on GPUs. • Ability to learn fast and quickly adapt to change. • Clear written and oral communications skills with the ability to effectively collaborate with executives and engineering teams. Ways to stand out from the crowd: • Experience with and/or contributions to open-source NVIDIA AI libraries and models, particularly Nemotron, NeMo, NeMo Framework, NeMo-RL. • Hands-on experience with data curation and analysis for model post-training and RL. • Prior experience with AI model training techniques applied to multi-modal data (audio, image, and video). • Knowledge of NVIDIA GPU/CPU architecture and its impact on software performance. • Show willingness and ability to dig into unfamiliar territories to solve complex problems relying on experience from previous work. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until August 28, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive 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.

Requirements

Must-haves

A huge part of our work involves developing end-to-end AI solutions for enterprise use cases. We help customers adopt NVIDIA AI models and libraries by offering deep technical expertise.
Tackle sophisticated AI challenges by applying skills across the AI model lifecycle—from data processing and orchestration to training, post-training, reinforcement learning (RL), evaluation, and model optimization.
Support a broad model portfolio spanning LLMs, multimodal, retrieval, speech, content safety, and edge use cases.
Partner with enterprise customers in co-design engagements — understanding their data, evaluation criteria, and success metrics to deliver customized AI solutions.
Strong foundational expertise, from a BS, MS, or Ph.D. degree in Engineering, Mathematics, Physics, Computer Science, Data Science, or similar (or equivalent experience).
5+ years of experience with AI frameworks such as PyTorch, JAX, or TensorFlow, and libraries like Hugging Face Transformers.
Proficiency in Python programming, software design, debugging, and performance analysis, with at least 5+ years of experience in a Linux environment.
Hands-on experience with AI model lifecycle, including evaluation, failure analysis, pre-training, post-training, RL, and model optimization.
Expertise in distributed computing methodologies, including model and data parallelism.
Experience with distributed computing tools, like SLURM and Kubernetes, for training and evaluating large models on GPUs.
Ability to learn fast and quickly adapt to change.
Clear written and oral communications skills with the ability to effectively collaborate with executives and engineering teams.
Experience with and/or contributions to open-source NVIDIA AI libraries and models, particularly Nemotron, NeMo, NeMo Framework, NeMo-RL.
Hands-on experience with data curation and analysis for model post-training and RL.
Prior experience with AI model training techniques applied to multi-modal data (audio, image, and video).
Knowledge of NVIDIA GPU/CPU architecture and its impact on software performance.
Show willingness and ability to dig into unfamiliar territories to solve complex problems relying on experience from previous work.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until August 28, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aipythonkubernetes

Platform: eightfold
Effort: medium

Benefits

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Vision