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Principal AI and ML Infra Software Engineer, GPU Clusters

Santa Clara, CA, US; Redmond, WA, US

Open 6 months, first seen by us 184 days ago
Pay
USD 272,000–431,250/year · BaseAnnual period assumed. Location-specific pay — pay source
NVIDIA offers competitive salaries and a comprehensive benefits package. Our engineering teams are growing rapidly due to outstanding expansion. If you're a passionate and independent engineer with a love for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD. You will also be eligible for equity and benefits.
Read the full posting
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting

What you’ll work on

Full posting
  • Turn AI/ML researchers' infrastructure needs and pain points into concrete improvements

  • Lead initiatives to find and fix researcher efficiency bottlenecks, setting long-term roadmaps

  • Monitor and optimize infrastructure for high availability, scalability and resource use

  • Define metrics for AI researcher efficiency and tie actions to measurable results

  • Build a cohesive AI/ML infrastructure ecosystem with researchers, data engineers and DevOps

From the employer’s posting
Engage closely with our AI and ML research teams to discern their infrastructure requirements and barriers, converting those insights into actionable improvements.
Proactively identify researcher efficiency bottlenecks and lead initiatives to systematically improve it. Drive the direction and long-term roadmaps for such initiatives.
Monitor and optimize the performance of our infrastructure ensuring high availability, scalability, and efficient resource utilization.
Help define and improve important measures of AI researcher efficiency, ensuring that our actions are in line with measurable results.
Work closely with a variety of teams, such as researchers, data engineers, and DevOps professionals, to develop a cohesive AI/ML infrastructure ecosystem.
Apply at NVIDIA

Posting record

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Open 6 monthsWe first saw this posting 184 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
May 12, 2026184 days ago
Recorded sightings
145
Last seen by us
Nov 11, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$166K–$240K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 1,383 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 184

Up longer than most. Similar jobs usually come down between day 8 and day 75.

Well past NVIDIA’s usual: its jobs come down by about day 32.

From 5,254 similar postings that came down, and 106 of NVIDIA’s. Coming down is not always a hire.

NVIDIA is hiring

104 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • ML Engineer hiring is steady
  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Bash
  • Python
  • AWS
  • Azure
  • Docker
  • GCP
  • Kubernetes
  • PyTorch
  • Go
Where the posting names them
* Capability in supervising and improving substantial distributed training operations using PyTorch (DDP, FSDP), NeMo, or JAX. Moreover, an in-depth understanding of AI/ML workflows, involving data processing, model training, and inference pipelines. * Proficiency in programming & scripting languages such as Python, Go, Bash, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) in addition to experience with parallel computing frameworks and paradigms. * Dedication to ongoing learning and staying updated on new technologies and innovative methods in the AI/ML infrastructure sector.
* 15+ years of demonstrated expertise in AI/ML and HPC tasks and systems. * Hands-on experience in using or operating High Performance Computing (HPC) grade infrastructure as well as in-depth knowledge of accelerated computing (e.g., GPU, custom silicon), storage (e.g., Lustre, GPFS, BeeGFS), scheduling & orchestration (e.g., Slurm, Kubernetes, LSF), high-speed networking (e.g., Infiniband, RoCE, Amazon EFA), and containers technologies (Docker, Enroot). * Capability in supervising and improving substantial distributed training operations using PyTorch (DDP, FSDP), NeMo, or JAX. Moreover, an in-depth understanding of AI/ML workflows, involving data processing, model training, and inference pipelines.
* Hands-on experience in using or operating High Performance Computing (HPC) grade infrastructure as well as in-depth knowledge of accelerated computing (e.g., GPU, custom silicon), storage (e.g., Lustre, GPFS, BeeGFS), scheduling & orchestration (e.g., Slurm, Kubernetes, LSF), high-speed networking (e.g., Infiniband, RoCE, Amazon EFA), and containers technologies (Docker, Enroot). * Capability in supervising and improving substantial distributed training operations using PyTorch (DDP, FSDP), NeMo, or JAX. Moreover, an in-depth understanding of AI/ML workflows, involving data processing, model training, and inference pipelines. * Proficiency in programming & scripting languages such as Python, Go, Bash, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) in addition to experience with parallel computing frameworks and paradigms.

Your next step

Complete your application on jobs.nvidia.com. The employer’s form will show what is required.

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About NVIDIA

People
About 42,000 in 2026, up 17% from the year before.Annual report (SEC Form 10-K)
Company
Listed as NVDA.
H-1B visas
978 approved for new hires in fiscal 2025.US Citizenship and Immigration Services

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 13% over the last 6 weeks compared with the 6 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 617, the most 1,122, and the latest week had 1,122.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

We are seeking a Principal AI and ML Infra Software Engineer, GPU Clusters at NVIDIA to join our Hardware Infrastructure team. As an Engineer, you will have a pivotal role in enhancing efficiency for our researchers by implementing progressions throughout the entire stack. Your main task will revolve around collaborating closely with customers to pinpoint and address infrastructure deficiencies, facilitating groundbreaking AI and ML research on GPU Clusters. Together, we can craft potent, effective, and scalable solutions as we mold the future of AI/ML technology! What you will be doing: * Engage closely with our AI and ML research teams to discern their infrastructure requirements and barriers, converting those insights into actionable improvements. * Proactively identify researcher efficiency bottlenecks and lead initiatives to systematically improve it. Drive the direction and long-term roadmaps for such initiatives. * Monitor and optimize the performance of our infrastructure ensuring high availability, scalability, and efficient resource utilization. * Help define and improve important measures of AI researcher efficiency, ensuring that our actions are in line with measurable results. * Work closely with a variety of teams, such as researchers, data engineers, and DevOps professionals, to develop a cohesive AI/ML infrastructure ecosystem. * Keep up to date with the most recent developments in AI/ML technologies, frameworks, and successful strategies, and advocate for their integration within the organization. What we need to see: * BS or similar background in Computer Science or related area (or equivalent experience). * 15+ years of demonstrated expertise in AI/ML and HPC tasks and systems. * Hands-on experience in using or operating High Performance Computing (HPC) grade infrastructure as well as in-depth knowledge of accelerated computing (e.g., GPU, custom silicon), storage (e.g., Lustre, GPFS, BeeGFS), scheduling & orchestration (e.g., Slurm, Kubernetes, LSF), high-speed networking (e.g., Infiniband, RoCE, Amazon EFA), and containers technologies (Docker, Enroot). * Capability in supervising and improving substantial distributed training operations using PyTorch (DDP, FSDP), NeMo, or JAX. Moreover, an in-depth understanding of AI/ML workflows, involving data processing, model training, and inference pipelines. * Proficiency in programming & scripting languages such as Python, Go, Bash, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) in addition to experience with parallel computing frameworks and paradigms. * Dedication to ongoing learning and staying updated on new technologies and innovative methods in the AI/ML infrastructure sector. * Excellent communication and collaboration skills, with the ability to work effectively with teams and individuals of different backgrounds. NVIDIA offers competitive salaries and a comprehensive benefits package. Our engineering teams are growing rapidly due to outstanding expansion. If you're a passionate and independent engineer with a love for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until November 3, 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.
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Pay
NVIDIA offers competitive salaries and a comprehensive benefits package. Our engineering teams are growing rapidly due to outstanding expansion. If you're a passionate and independent engineer with a love for technology, we want to hear from you. Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD. You will also be eligible for equity and benefits.
Location & working pattern

Santa Clara, CA, US; Redmond, WA, US

Working pattern and location restrictions need checking in the full posting.

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