Pay
$166K–$240K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 1,279 postings in the last year. Stated ranges, not salaries paid.
ML Infrastructure Engineer
Amsterdam, Netherlands; Remote - Europe; Remote - United States
Open 5 months, first seen by us 175 days ago- Pay
- Pay not listedSimilar roles state $166K–$240K
- Work setting
Remote — work setting source
Listed location: Amsterdam, Netherlands; Remote - Europe; Remote - United States
Read the full posting- Employment
- Not stated
What you’ll work on
Full postingProfile and analyse GPU performance at system and kernel level with hardware teams
Compare GPU performance across platforms, architectures and software stacks like CUDA and ROCm
Debug and optimise ML workloads to remove performance bottlenecks on GPUs
Run acceptance tests on new GPU clusters for performance, stability and compatibility
Build tools and dashboards to visualise performance metrics, bottlenecks and trends
From the employer’s posting
profile and analyse GPU performance at the system and kernel level
Evaluate and compare GPU performance across different platforms, architectures, and software stacks (e.g.,CUDA, ROCm)
Debug and optimise ML workloads to run efficiently on GPU hardware, identifying and resolving performance bottlenecks
Perform acceptance testing acceptance testing for new GPU clusters, ensuring hardware and software meet performance, stability, and compatibility requirements for AI workloads
Develop tools and dashboards to visualise performance metrics visualise performance metrics, bottlenecks, and trends
About Nebius
Nebius is leading a new era in cloud infrastructure for the global AI economy.
In the employer’s words · Read in context
Posting record
Report an errorOpen 5 monthsWe first saw this posting 175 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, 2026175 days ago
- Recorded sightings
- 246
- Last seen by us
- Nov 4, 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
Time since we first saw it
Day 175
Up longer than most. Similar jobs usually come down between day 6 and day 69.
From 4,284 similar postings that came down. Coming down is not always a hire.
Nebius is hiring
17 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- ML Engineer hiring has slowed
- Its jobs tend to stay up a long time
- 12% of open jobs were reposted
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.
- Python
- AWS
- Azure
- Docker
- GCP
- Kubernetes
- PyTorch
Where the posting names them
- Familiarity with modern LLM inference frameworks (vLLM, SGLang, TensorRT) - Experience in Python and performance profiling tools (e.g., Nsight, nvprof, perf). - Familiarity with cloud ML platforms like AWS, GCP, Azure ML
- Experience in Python and performance profiling tools (e.g., Nsight, nvprof, perf). - Familiarity with cloud ML platforms like AWS, GCP, Azure ML - Contributions to open-source ML benchmarking tools
- Good understanding of the GPU stack: CUDA,NCCL, drivers, and relevant libraries - Familiarity with containerized environments (e.g., Docker, Kubernetes). - Strong communication and ability to work independently
- Deep understanding of performance aspects of large neural networks training and inference (data/tensor/context/expert parallelism, offloading, custom kernels, hardware features, attention optimisations, dynamic batching etc.) - Deep experience with modern deep learning frameworks (PyTorch, JAX, Megatron-LM, Tensort-LLM) - Good understanding of the GPU stack: CUDA,NCCL, drivers, and relevant libraries
Your next step
Complete your application on careers.nebius.com. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
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
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
The role
We are seeking a highly skilled ML/AI Engineer to join our team to lead and support benchmarking of GPU platforms benchmarking of GPU platforms for machine learning and AI workloads. You will play a critical role in evaluating the performance of GPU-based hardware for various deep learning and AI frameworks, enabling data-driven decisions for platform optimisation and next-generation hardware development.
Your responsibilities will include:
- Work closely with hardware, development teams to profile and analyse GPU performance at the system and kernel level.
- Evaluate and compare GPU performance across different platforms, architectures, and software stacks (e.g.,CUDA, ROCm).
- Debug and optimise ML workloads to run efficiently on GPU hardware, identifying and resolving performance bottlenecks.
- Perform acceptance testing acceptance testing for new GPU clusters, ensuring hardware and software meet performance, stability, and compatibility requirements for AI workloads.
- Perform experiments across diverse GPU system configurations to assess the impact of varying interconnect strategies and system-level optimisations on performance and scalability.
- Develop tools and dashboards to visualise performance metrics visualise performance metrics, bottlenecks, and trends.
- Contribute to internal tooling, frameworks, and best practices
We expect you to have:
- A profound understanding of theoretical foundations of machine learning
- Deep understanding of performance aspects of large neural networks training and inference (data/tensor/context/expert parallelism, offloading, custom kernels, hardware features, attention optimisations, dynamic batching etc.)
- Deep experience with modern deep learning frameworks (PyTorch, JAX, Megatron-LM, Tensort-LLM)
- Good understanding of the GPU stack: CUDA,NCCL, drivers, and relevant libraries
- Familiarity with containerized environments (e.g., Docker, Kubernetes).
- Strong communication and ability to work independently
Ways to stand out from the crowd:
- Familiarity with modern LLM inference frameworks (vLLM, SGLang, TensorRT)
- Experience in Python and performance profiling tools (e.g., Nsight, nvprof, perf).
- Familiarity with cloud ML platforms like AWS, GCP, Azure ML
- Contributions to open-source ML benchmarking tools
Benefits & Perks:
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and ownership
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.
If you need accommodations during the application process, please let us know.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Amsterdam, Netherlands; Remote - Europe; Remote - United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.