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Senior Solutions Architect, AI Hyperscalers

Updated

$184,000–$356,500annualizedRemote, hiring in CaliforniaSenior

NVIDIA seeks a Senior Solutions Architect to lead technical engagement with hyperscale cloud customers, driving adoption of NVIDIA's AI/ML infrastructure at massive scale.

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View posting at NVIDIA

At a glance

Posted base pay

$184K–$357KAbove the median

The work

Integrates and configures it

Balance

  1. Mostly building
  2. Mixed
  3. Mostly pre-sales or support

Project stages

  1. Pre-sales
  2. Proof of concept
  3. Implementation
  4. Operations
Coding
Writes production code
Builds for
External customers
Level
Senior
Role
Technical lead

What they ask for

Experience

  • 8+ yearsengineering experience with AI/ML-focused projects or enterprise-grade solutions

Background

  • Software engineering

Tools

  • Python
  • CUDA
  • PyTorch
  • JAX
  • Docker
  • Kubernetes
  • Linux
  • RAG
  • vector databases
  • HPC

Less common in FDE jobs

  • Covers pre-sales24%
  • Fully remote28%
  • Company stage: Public33%
  • Company size: About 5,000+ people38%

Share of US FDE postings that state each fact.

The job description from NVIDIA

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by extraordinary technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing.

NVIDIA is searching for an AI/ML Solutions Architect focusing on Hyperscale customers and Cloud Service Providers. Your primary responsibilities will be to lead software customer technical engagement for AI training, inference and infrastructure being deployed at vast scale. You will work across multiple organizations within NVIDIA as well as at the customer to ensure successful and trouble-free deployments. If you would you like to partner with a large company to build automation and management to create a robust large scale artificial intelligence infrastructure and are interested in the optimization and characterization of customer specific AI models and pipelines - you should apply!

What you’ll be doing

  • As a key technical member of a focused account team, you will serve as the main point of contact for NVIDIA products, enabling internet giants and cloud providers to have an innovative AI/ML software infrastructure.
  • Work directly with best-in-class engineering teams to secure design wins, address challenges, bring solutions to production, and support them throughout their lifecycle.
  • Become a trusted advisor to your customer by understanding their environment, constraints, and long-term strategy. Translate these insights into product requirements and innovative solutions.
  • Help your customer enhance the value of NVIDIA technology, and provide feedback to NVIDIA for future product improvements.
  • Facilitate the resolution of customer issues, offering timely and proactive communications to mitigate risks.
  • Lead workshops, demos, and proof-of-concepts to showcase NVIDIA’s AI/ML capabilities.
  • Guide customers on standard processes for scalable AI model deployment and inference optimization.

What we need to see

  • Minimum of a BS/MS in Computer Science, Electrical Engineering, or equivalent experience.
  • 8+ years of engineering experience with a proven track record in AI/ML-focused projects or enterprise-grade solutions.
  • Proven understanding of Linux, including solving, optimization, and customization for AI/ML workloads.
  • Strong understanding of data science and machine learning infrastructure—software and hardware.
  • Professional-level communication skills, including the ability to tailor messages for varying technical audiences and maintain composure in high-pressure situations.
  • Excellent follow-up and interpersonal skills, with a true passion for problem-solving.
  • Proficient in Python, with the ability to develop scripts and build custom tools. Experience with parallel programming or GPU acceleration (e.g., CUDA) is helpful.
  • Shown eagerness to learn and apply new technologies.

Ways to stand out from the crowd

  • Experience with Chatbots, RAG pipelines, vector databases, and distributed training or inference workloads.
  • Experience or background in HPC (High Performance Computing) environments for AI or ML applications.
  • Familiarity with multi-node GPU clusters and performance tuning for large-scale AI workloads.
  • Experience developing in cloud and/or virtualized environments, containerized solutions, with knowledge of Docker, Kubernetes
  • Background with common deep learning frameworks such as PyTorch or JAX.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 17, 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 posting at NVIDIA

About NVIDIA

Full-stack accelerated computing and AI infrastructure company building GPUs, CPUs, networking, systems, software and platforms for data centers, gaming, professional visualization, automotive and robotics.

Public · 5000+ people

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Pay and conditions

Posted pay
$184,000–$356,500Annualized in US dollars
Location
Santa Clara, CA
Work arrangement
Remote
Remote work restrictions
California, US
Employment type
Full-time
Experience requirements
  • 8+ years: engineering experience with AI/ML-focused projects or enterprise-grade solutions (required)