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.
Santa Clara, CA, US; Redmond, WA, US
Open 6 months, first seen by us 184 days agoNVIDIA 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
Employment type in the employer’s posting: FULL_TIMEFrom the employer’s 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
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.
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.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$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.
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.
104 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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.
* 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.
Complete your application on jobs.nvidia.com. The employer’s form will show what is required.
Already applied? Track this application
New ML Engineer postings at the employers we follow are up 13% over the last 6 weeks compared with the 6 before.
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.
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.
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.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
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.
Santa Clara, CA, US; Redmond, WA, US
Working pattern and location restrictions need checking in the full posting.
No clear work-authorization passage found. Eligibility is unconfirmed.