Senior Solutions Architect

Nvidia

Confirmed live yesterday Trusted

Remote

Quick summary

Work type: Remote
Location: Remote
Salary: $184,000–$287,500 / yr
Posted: 14 days ago
Freshness: Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $208k

This role $236k

$162k most similar roles pay here $301k

This role pays more than 74% of similar roles. Most pay $177,683–$237,500 — the shaded band above. At the midpoint, this role pays about $236k versus about $208k for comparable roles.

Based on 239 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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View all roles at Nvidia

At a glance

TL;DR · Senior Solutions Architect

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Senior Solutions Architect, NVIDIA Cloud Partners serves as a trusted technical advisor and primary driver for customers during the design, development, construction, integration, and production of GPU cloud infrastructure and applications. Working within an interdisciplinary team, you will collaborate with partners to deliver hardware and software solutions, conduct technical meetings, and create content like reference architectures and workshops. The role focuses on solving complex problems in large-scale AI and HPC GPU infrastructure by integrating libraries, frameworks, models, and software applications to drive consumption. You will utilize Python, PyTorch, TensorFlow, and specialized tools such as TensorRT-LLM, Triton Inference Server, and the NeMo Framework. Key technical domains include Deep Learning, LLMs, MLOps, cluster orchestration using SLURM or K8s, and experience with distributed cloud architectures across AWS, Azure, and GCP environments.

What does a Solutions Architect earn in Remote?

Median $231100 from 71 postings across 13 companies.

See salary data

Skills

Python PyTorch TensorFlow CUDA NVIDIA Triton Inference Server TensorRT TensorRT-LLM MLOps SLURM AWS Azure GCP Deep Learning LLMs HPC NCCL DCGM UFM

What you'll do

Act as a technical advisor to bridge the gap between design and deployment of large-scale AI/HPC GPU infrastructure.
Drive hardware and software consumption by integrating libraries, frameworks, models, and applications into customer workflows.
Serve as the primary technical driver for customers during the construction and integration of GPU cloud infrastructure.
Conduct technical meetings to discuss product features, introduce new technologies, and lead debugging sessions.
Develop and deliver technical content including presentations, workshops, reference architectures, and tutorials for customers.
Build and implement Proofs of Concept (PoCs) to address critical customer business needs regarding infrastructure and software stacks.
Provide product strategy recommendations based on direct feedback from strategic customers and partners.

What we're looking for

BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, Mathematics, or a related engineering field or equivalent experience.
10+ years of Solution Engineering, Sales Engineering, Cloud Engineering, or Solution Architecture experience working with partners and customers.
Experience crafting and deploying large-scale cluster environments and designing distributed cloud architectures.
Strong programming fundamentals in Python and deep learning frameworks such as PyTorch and TensorFlow.
Practical expertise in fine-tuning models and integrating software application stacks to drive GPU platform consumption.
Proficiency in large-scale AI model training, deployment, MLOps, and cluster orchestration using tools like SLURM or K8s.
Experience with NVIDIA hardware, software libraries (TensorRT, Triton), and cloud environments (AWS, Azure, GCP).
Excellent communication, presentation, and collaboration skills to manage complex multi-disciplinary technical engagements.

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