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Machine Learning Engineer
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Work setup in the employer’s posting: hybrid
From the employer’s posting- Employment
- Not stated
What you’ll work on
Full postingDesign and build real-time ML services for ad floor pricing, ad load and in-game personalization
Build data pipelines and performant queries over large-scale behavioral data
Take models from research to production with Data Scientists and own the production side
Set up CI/CD, monitoring and model quality tracking
From the employer’s posting
Designing and building real-time ML services for ads monetization (floor pricing, ad load) and in-game personalization (difficulty, content)
Building data pipelines and performant queries over large-scale behavioral data
Taking models from research to production together with DS: shaping requirements, agreeing on interfaces, and owning the production part
Setting up CI/CD, monitoring and model quality tracking
What you’ll bring
All qualificationsCore experience
- Experience building and running production services in Python, including performance optimization
- Strong SQL and hands-on experience with large data volumes
- Experience in data engineering and MLOps (pipelines, CI/CD, monitoring)
- Understanding of ML and A/B testing enough to work on equal terms with Data Scientists
- Fluent Russian
Qualification wording
Experience building and running production services in Python, including performance optimization
Strong SQL and hands-on experience with large data volumes
Experience in data engineering and MLOps (pipelines, CI/CD, monitoring)
Understanding of ML and A/B testing well enough to work on equal terms with DS
Fluent Russian is required
Tools in this posting
- Python
- SQL
- ClickHouse
- Docker
- MLflow
- PostgreSQL
- Airflow
- LightGBM
- PyTorch
Source — Tool mentions in context
Responsibilities: - Designing and building real-time ML services for ads monetization (floor pricing, ad load) and in-game personalization (difficulty, content); - Building data pipelines and performant queries over large-scale behavioral data; - Taking models from research to production together with DS: shaping requirements, agreeing on interfaces, and owning the production part; - Setting up CI/CD, monitoring and model quality tracking. Tech stack: Python, ClickHouse, PostgreSQL, Airflow, MLflow, Docker; PyTorch and LightGBM models in production. Requirements: - Experience building and running production services in Python, including performance optimization; - Strong SQL and hands-on experience with large data volumes; - Experience in data engineering and MLOps (pipelines, CI/CD, monitoring); - Understanding of ML and A/B testing well enough to work on equal terms with DS; - Ability to understand business context, gather requirements and own technical decisions; - Experience with high-load or low-latency systems, ad tech, or mobile games is a plus; - B2+ level of English; - Fluent Russian is required.
Tech stack: Python, ClickHouse, PostgreSQL, Airflow, MLflow, Docker; PyTorch and LightGBM models in production. Requirements: - Experience building and running production services in Python, including performance optimization; - Strong SQL and hands-on experience with large data volumes; - Experience in data engineering and MLOps (pipelines, CI/CD, monitoring); - Understanding of ML and A/B testing well enough to work on equal terms with DS; - Ability to understand business context, gather requirements and own technical decisions; - Experience with high-load or low-latency systems, ad tech, or mobile games is a plus; - B2+ level of English; - Fluent Russian is required. Benefits: Besides the engaging tasks, support from experienced colleagues, challenge, and drive, we offer: - Full support in relocating to countries where our offices are located; - High-end market salary with performance bonuses; - All needed equipment; - Regular company events and monthly Friday meetings; - Social benefits (private medical cover, sports reimbursement, etc.); - Paid vacations, sick days; - English, Greek, and Polish online language classes; - Reimbursement for education and professional development.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Sep 26, 202640 days ago
- Recorded sightings
- 26
- Last seen by us
- Nov 5, 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
Easybrain is hiring
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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Demand for ML Engineer roles
New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 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
Easybrain is looking for a Machine Learning Engineer to join our Business Intelligence team. Our ML models run in production, powering LTV prediction and user acquisition optimization across a portfolio of games with billions of installs. We are now building new ML systems for ads monetization and game personalization, and many of them make decisions in real time.You will work alongside Data Scientists as an equal partner and own the engineering side of these systems: real-time services, data pipelines, and deployment and monitoring infrastructure. The role combines backend development, data engineering and MLOps, with a lot of work on large-scale data.
Responsibilities:
- Designing and building real-time ML services for ads monetization (floor pricing, ad load) and in-game personalization (difficulty, content);
- Building data pipelines and performant queries over large-scale behavioral data;
- Taking models from research to production together with DS: shaping requirements, agreeing on interfaces, and owning the production part;
- Setting up CI/CD, monitoring and model quality tracking.
Tech stack: Python, ClickHouse, PostgreSQL, Airflow, MLflow, Docker; PyTorch and LightGBM models in production.
Requirements:
- Experience building and running production services in Python, including performance optimization;
- Strong SQL and hands-on experience with large data volumes;
- Experience in data engineering and MLOps (pipelines, CI/CD, monitoring);
- Understanding of ML and A/B testing well enough to work on equal terms with DS;
- Ability to understand business context, gather requirements and own technical decisions;
- Experience with high-load or low-latency systems, ad tech, or mobile games is a plus;
- B2+ level of English;
- Fluent Russian is required.
Benefits:
Besides the engaging tasks, support from experienced colleagues, challenge, and drive, we offer:
- Full support in relocating to countries where our offices are located;
- High-end market salary with performance bonuses;
- All needed equipment;
- Regular company events and monthly Friday meetings;
- Social benefits (private medical cover, sports reimbursement, etc.);
- Paid vacations, sick days;
- English, Greek, and Polish online language classes;
- Reimbursement for education and professional development.
Employment type
Data Science
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
Limassol
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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