Solutions Architect, Inference Deployments at NVIDIA

You are a solutions architect with at least five years of experience building distributed systems and deploying AI inference workloads on Kubernetes. You hold a

Work type: onsite

Location: US, CA, Santa Clara

Salary: $152,000 – $287,500/yr

Type: Full-time

Summary

You are a solutions architect with at least five years of experience building distributed systems and deploying AI inference workloads on Kubernetes. You hold a bachelor’s degree in computer science or engineering and possess deep technical expertise in GPU orchestration and model optimization. **What makes it worth a look...** NVIDIA offers a base salary between $152,000 and $287,500 depending on the level, plus equity and benefits for this on-site role in Santa Clara, California. This is a rare chance to work directly on high-performance generative AI pipelines using proprietary GPU technology. **You might be a good fit if you...** * Have hands-on experience with NVIDIA Dynamo, Triton Inference Server, or TensorRT-LLM. * Can manage complex GPU memory hierarchies and low-latency networking like RDMA or UCX. * Possess deep knowledge of Kubernetes operations including MIG partitioning and the GPU Operator. * Have a proven history of tuning large language models for production enterprise environments.

Job Description

We’re forming a team of innovators to roll out and enhance AI inference solutions at scale, demonstrating NVIDIA’s GPU technology and Kubernetes. As a Solutions Architect focused on inference, you’ll collaborate closely with our engineering, DevOps, and customers to develop enterprise AI solutions. Together, we'll deliver generative AI to production!

What you'll be doing:

• Build inference pipelines with tools like NVIDIA Dynamo, distributing tasks among GPU workers to improve efficiency.

• Collaborate with DevOps teams to orchestrate disaggregated inference using Kubernetes for complex workloads.

• Accelerate inference pipelines using TensorRT-LLM, vLLM, SGLang, and other backends to ensure seamless integration with disaggregated inference.

• Provide mentorship and technical leadership to customers and internal teams, guiding them through the deployment of disaggregated inference systems and resolving complex issues.

• 5+ Years in Solutions Architecture with a proven track record of deploying distributed systems and AI inference workloads on Kubernetes.

• Experience with one of NVIDIA Dynamo, Triton Inference Server, or TensorRT-LLM for model optimization and serving.

• GPU orchestration using NVIDIA GPU Operator, NIM Operator, and Multi-Instance GPU (MIG) partitioning.

• Solving sophisticated GPU allocation, memory hierarchies (HBM, DRAM, SSD), and low-latency networking (RDMA, UCX).

• Demonstrated success in tuning large language models for low-latency inference in enterprise environments.

• BS in CS/Engineering or equivalent experience.

• Prior experience deploying NVIDIA inference technologies such as Dynamo, NIM, NIXL and Grove.

• Deep understanding of transformer neural network, and inference acceleration technologies like quantization, speculative decoding, WideEP etc.

• NVIDIA Certified AI Engineer or similar credentials.

• Contributions to open-source projects including NVIDIA Dynamo, vLLM, KServe, or SGLang.

You will also be eligible for equity and [benefits](https://www.nvidia.com/en-us/benefits/).

Applications for this job will be accepted at least until April 19, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

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.

View this job on nocollar jobs