Time since we first saw it
Day 17
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.
Senior ML Engineer (Agentic Search)
Amsterdam, Netherlands; London, United Kingdom; Remote - Europe; Zurich, Switzerland
Live, first seen by us 17 days ago- Pay
- Pay not listed
- Work setting
Remote — work setting source
Listed location: Amsterdam, Netherlands; London, United Kingdom; Remote - Europe; Zurich, Switzerland
Read the full posting- Employment
- Not stated
What you’ll work on
Full postingDevelop models supporting crawling, data selection, and content understanding
Build and maintain the data, training and evaluation pipelines behind our models: training-data generation, evaluation sets and retraining
Work closely with engineering to integrate and deploy ML models in production services, balancing latency, quality and cost
From the employer’s posting
Train and deploy ML models for retrieval, reranking, and search relevance, such as embedding models and cross-encoders, in production Develop models supporting crawling, data selection, and content understanding Build and maintain the data, training and evaluation pipelines behind our models: training-data generation, evaluation sets and retraining
Develop models supporting crawling, data selection, and content understanding Build and maintain the data, training and evaluation pipelines behind our models: training-data generation, evaluation sets and retraining Contribute to and improve our ML platform: training and orchestration workflows (Kubernetes, GPU scheduling, experiment tracking, model lifecycle) and inference optimisation for low-latency serving
Contribute to and improve our ML platform: training and orchestration workflows (Kubernetes, GPU scheduling, experiment tracking, model lifecycle) and inference optimisation for low-latency serving Work closely with engineering to integrate and deploy ML models in production services, balancing latency, quality and cost Apply the latest architectural advances and training procedures for retrieval and LLM-integrated systems
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 error- Status in our records
- Live
- First seen by us
- Oct 18, 202617 days ago
- Recorded sightings
- 75
- Last seen by us
- Nov 4, 2026
- Reposted
- once since Apr 14, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
How this job compares
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.
- C++
- Python
- Kubernetes
- Hugging Face
- Go
Where the posting names them
- 5+ years of experience in software engineering or applied machine learning - Strong programming skills in Python and at least one of Go or C++ - Proven experience deploying ML models in production systems
- Build and maintain the data, training and evaluation pipelines behind our models: training-data generation, evaluation sets and retraining - Contribute to and improve our ML platform: training and orchestration workflows (Kubernetes, GPU scheduling, experiment tracking, model lifecycle) and inference optimisation for low-latency serving - Work closely with engineering to integrate and deploy ML models in production services, balancing latency, quality and cost
- Hands-on experience with retrieval, ranking, or recommendation - Experience with Kubernetes, distributed training or GPU scheduling, or inference optimisation (batching, quantisation, compilation) - Contributions to open-source projects, technical publications, or conference talks
- Contributions to open-source projects, technical publications, or conference talks - Strong results on public benchmarks or leaderboards (e.g. MTEB, BEIR) or models released on Hugging Face Benefits & Perks:
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
Has Nebius posted this job before?
Yes. We’ve followed 2 other Senior ML Engineer (Agentic Search) jobs there since April 2026. 2 came down, usually after about 103 days.
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.
We are seeking a Senior ML Engineer to join a fast-growing team building an agent-native search platform for AI systems, the emerging web access layer for AI. Our focus is agentic search, where AI systems plan, retrieve and refine rather than just return results.
You will develop and deploy machine learning models that power retrieval, ranking, and indexing at scale, helping AI systems access fresh, reliable information in real time.
This is a high-impact role working on a production system used 24x7, operating at the scale of web search.
Your responsibilities:
-
Train and deploy ML models for retrieval, reranking, and search relevance, such as embedding models and cross-encoders, in production
-
Develop models supporting crawling, data selection, and content understanding
-
Build and maintain the data, training and evaluation pipelines behind our models: training-data generation, evaluation sets and retraining
-
Contribute to and improve our ML platform: training and orchestration workflows (Kubernetes, GPU scheduling, experiment tracking, model lifecycle) and inference optimisation for low-latency serving
-
Work closely with engineering to integrate and deploy ML models in production services, balancing latency, quality and cost
-
Apply the latest architectural advances and training procedures for retrieval and LLM-integrated systems
Must-haves:
-
5+ years of experience in software engineering or applied machine learning
-
Strong programming skills in Python and at least one of Go or C++
-
Proven experience deploying ML models in production systems
-
Solid understanding of machine learning and modern deep learning, including transformers and embeddings
-
Experience building data or ML pipelines and working with workflow orchestration
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Ability to define meaningful model metrics and evaluate models rigorously
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Product-oriented mindset with a focus on impact and iteration
Nice-to-haves:
-
Hands-on experience with retrieval, ranking, or recommendation
-
Experience with Kubernetes, distributed training or GPU scheduling, or inference optimisation (batching, quantisation, compilation)
-
Contributions to open-source projects, technical publications, or conference talks
-
Strong results on public benchmarks or leaderboards (e.g. MTEB, BEIR) or models released on Hugging Face
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; London, United Kingdom; Remote - Europe; Zurich, Switzerland
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.