Solutions Architect, AI and ML

Posted 2 Days Ago
Be an Early Applicant
3 Locations
In-Office
120K-236K
Mid level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The Solutions Architect will support customers in deploying GPU-accelerated ML solutions on cloud platforms and provide technical mentorship, enhancing AI inference pipelines, and collaborating with engineering teams to optimize deployments.
Summary Generated by Built In

NVIDIA is building the world’s leading AI company, and we are looking for an experienced Cloud Solution Architect to help assist customers with adoption of GPU hardware and Software, as well as building and deploying Machine Learning (ML) , Deep Learning (DL), data analytics solutions on various Cloud Computing Platforms. As part of the Solutions Architecture team, we work with some of the most exciting computing hardware and software technologies including the latest breakthroughs in machine learning and data science. A Solutions Architect is the first line of technical expertise between NVIDIA and our customers so you will engage directly with developers, researchers, and data scientists with some of NVIDIA’s most strategic technology customers as well as work directly with business and engineering teams on product strategy. We are looking for a Solutions Architect to help drive end-to-end technology solutions applying NVIDIA’s full set of technologies based on business needs of customers. Join us in this exciting endeavor!

What you will be doing:

  • Help cloud customers craft, deploy, and maintain scalable, GPU-accelerated inference pipelines on cloud ML services and Kubernetes for large language models (LLMs) and generative AI workloads.

  • Enhance performance tuning using TensorRT/TensorRT-LLM, vLLM, Dynamo, and Triton Inference Server to improve GPU utilization and model efficiency.

  • Collaborate with multi-functional teams (engineering, product) and offer technical mentorship to cloud customers implementing AI inference at scale.

  • Build custom PoCs for solution that address customer’s critical business needs applying NVIDIA hardware and software technology

  • Partner with Sales Account Managers or Developer Relations Managers to identify and secure new business opportunities for NVIDIA products and solutions for ML/DL and other software solutions

  • Prepare and deliver technical content to customers including presentations about purpose-built solutions, workshops about NVIDIA products and solutions, etc.

  • Conduct regular technical customer meetings for project/product roadmap, feature discussions, and intro to new technologies. Establish close technical ties to the customer to facilitate rapid resolution of customer issues

What we need to see:

  • BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Statistics, Physics, or other Engineering fields or equivalent experience.

  • 3+ Years in Solutions Architecture with a proven track record of moving AI inference from POC to production in cloud computing environments including AWS, GCP, or Azure

  • 3+ years of hands-on experience with Deep Learning frameworks such as PyTorch and TensorFlow

  • Excellent knowledge of the theory and practice of LLM and DL inference

  • Strong fundamentals in programming, optimizations, and software design, especially in Python

  • Experience with containerization and orchestration technologies like Docker and Kubernetes, monitoring, and observability solutions for AI deployments

  • Knowledge of Inference technologies - NVIDIA NIM, TensorRT-LLM, Dynamo, Triton Inference Server, vLLM, etc

  • Proficiency in problem-solving and debugging skills in GPU environments

  • Excellent presentation, communication and collaboration skills

Ways to stand out from the crowd:

  • AWS, GCP or Azure Professional Solution Architect Certification.

  • Experience optimizing and deploying large MoE LLMs at scale

  • Active contributions to open-source AI inference projects (e.g., vLLM, TensorRT-LLM Dynamo, SGLang, Triton or similar)

  • Experience with Multi-GPU Multi-node Inference technologies like Tensor Parallelism/Expert Parallelism, Disaggregated Serving, LWS, MPI, EFA/Infiniband, NVLink/PCIe, etc

  • Experience in developing and integrating monitoring and alerting solutions using Prometheus, Grafana, and NVIDIA DCGM and GPU performance Analysis and tools like NVIDIA Nsight Systems 

We make extensive use of conferencing tools, but occasional travel is required for local on-site visit to customers and industry events. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 120,000 USD - 189,750 USD for Level 2, and 148,000 USD - 235,750 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 21, 2025.NVIDIA is committed to fostering 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.

Top Skills

AWS
Azure
Cloud Computing
Deep Learning
Docker
Dynamo
GCP
Gpu
Grafana
Kubernetes
Machine Learning
Prometheus
Python
PyTorch
TensorFlow
Tensorrt
Triton Inference Server
Vllm
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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

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.”

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