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Why this grade This listing scored 57/100, which is a C. It lost the most ground on pay transparency. See the breakdown
- Description depth 20 / 20 How much the posting actually says about the work, measured in characters of real text.
- Freshness 12 / 15 How recently it was posted. Older postings are likelier to be filled or abandoned.
- Pay transparency 12 / 25 A published salary range, worth more than any other single factor because it is what a candidate cannot find out without applying.
- Remote clarity 8 / 15 Whether "remote" means anywhere, or is quietly restricted to one country.
- Corroboration 5 / 10 Whether more than one source carries this listing.
- Role specificity 0 / 10 Whether the listing is tagged well enough to tell what the role actually is.
Every figure above is arithmetic over the posting itself — its salary field, its text, its age, its tags and how many sources carry it. How the grades work →
NVIDIA is at the forefront of innovations in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention—the GPU—functions as the visual cortex of modern computing and is central to groundbreaking applications from generative AI to autonomous vehicles. We are now looking for a Software Engineer to help accelerate the next era of machine learning innovation.
In this role, you will propose and implement engineering solutions to ensure delivery of functional, reliable, secure, and performance-optimal GPU clusters to internal researchers, enable them to focus on training and development by reducing operational disruption and overhead, empower them for self-service continuous improvement on reliability, operational excellence & performance. Your work will empower scientists and engineers to train, fine-tune, and deploy the most advanced ML models on some of the world’s most powerful GPU systems.
What You'll Be Doing:
In this position, you will work with coworkers across the AI Platform organization to understand the pain points of validating, monitoring and operating GPU clusters at scale. Then you will design, develop and maintain engineering solutions to solve those pain points systematically.
You will also research in traditional AIOps and the emerging Agentic AI, and leverage it to further reduce the operation toil.
You will participate in on-call support for systems, platforms built and owned by the team.
What We Need To See:
BS/MS in Computer Science, Engineering, or equivalent experience.
2+ years in software/platform engineering, including 1 year in ML infrastructure or distributed systems.
Experience in software development lifecycle on Linux-based platforms.
Strong coding skills in languages such as Python, C++ or Rust.
Experience with Docker, Kubernetes, GitLab CI, automated deployments.
Experience with AIOps or Agentic AI and apply it successfully in production environment.
Ways To Stand Out From The Crowd:
Proficiency with full-stack development: Relational Data Modeling, DB optimization, REST API Semantics, Javascript, CSS, providing API as a service.
Passion for building developer-centric platforms with great UX and strong operational reliability.
Experience running Slurm or custom scheduling frameworks in production ML environments.
Familiarity with GPU computing, Linux systems internals, and performance tuning at scale.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until September 12, 2026.This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive 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.Originally posted on Himalayas
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Where this listing came from
- 10 Sep 2026 Himalayas first sighting
Seen on 1 board over 0 days.