Hiring.Camp

Software Solutions Architect - NVIS

Nvidia

·

Apr 15, 2026

Location
US, CA, Santa Clara, United States of America · US, TX, Remote
Workplace
Remote
Type
Full-time
Department
Engineering
Experience
5+ years
Education
Bachelor
Source
Workday

Description

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 great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

At NVIDIA, we are working with the latest technology, pushing boundaries and redefining what’s possible in the world of AI. Our team is passionate, driven, and committed to solving the most challenging problems with innovative solutions. As a Software Solution Architect for NVIS, you will play a crucial role in helping us build and deploy world-class AI and machine learning solutions. Join us in Israel and be part of a team that is making a significant impact on the future of computing!

What you'll be doing:

  • Helping our customers deploy cloud-native software stacks, such as NVIDIA AI, to embed guidelines in machine learning operations.

  • Collaborating closely with infrastructure admins, data scientists, and ML engineers to deploy tools like NVIDIA Run:ai and NVIDIA Mission Control.

  • Integrating NVIDIA software into customers’ existing ML ops environments and developing scripts to streamline these processes.

  • Diagnosing and resolving customer issues within sophisticated cloud-native environments, applying profiling and analysis tools to improve deep learning model performance.

  • Working with internal collaborators, including Pre-Sales Solution Engineers, Account Managers, and Product teams, to understand business requirements and provide technical insights.

  • Developing new tools and scripts to facilitate seamless integration with other Data Science tools.

What we need to see:

  • A minimum of 5 years of experience in a customer-facing role.

  • A B.Sc in Computer Science or equivalent experience.

  • Proven experience presenting to technical audiences and crafting technical content for developers.

  • Proficiency in Linux/Unix Operating Systems.

  • Hands-on experience with Kubernetes and containerization technologies like Docker.

  • Demonstrated experience in software development.

  • Certification as a Kubernetes Administrator (CKA).

  • Experience with AI and ML tools.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

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 for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and 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.

Skills

DockerKubernetesLinuxMachine LearningDeep LearningData Science

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