Time since we first saw it
Day 75
Up longer than most. Similar jobs usually come down between day 6 and day 70.
From 4,442 similar postings that came down. Coming down is not always a hire.
Reads like a ML Engineer role: putting models into production.
Work setup in the employer’s posting: hybridFrom the employer’s posting
Research and develop ads monetization optimization such as floor pricing and ad load balancing
Predict LTV and other key user metrics from large-scale behavioral data
Build in-game personalization systems for difficulty and content management
Validate models through A/B tests and bring them to production
Researching and developing ads monetization optimization (floor pricing, ad load balancing)
Predicting LTV and other key user metrics using large-scale behavioral data
Building in-game personalization systems: difficulty and content management
Validating models through A/B tests in collaboration with the analytical team and bringing them to production
Experience in predictive modelling and deploying ML models to production
Strong knowledge of Python and hands-on experience with the modern ML stack
Profound understanding of statistics and machine learning
B2+ level of English
Fluent Russian is required
Experience in reinforcement learning, recommender systems, ad tech, or mobile games is a plus
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 75
Up longer than most. Similar jobs usually come down between day 6 and day 70.
From 4,442 similar postings that came down. Coming down is not always a hire.
3 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd 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.
Responsibilities: - Researching and developing ads monetization optimization (floor pricing, ad load balancing) - an open research problem: from studying the underlying dynamics and simple heuristics to ML models and potentially RL; - Predicting LTV and other key user metrics using large-scale behavioral data: improving forecast accuracy through new modeling approaches, data signals, and features; - Building in-game personalization systems: difficulty and content management; - Validating models through A/B tests in collaboration with the analytical team and bringing them to production. Tech stack: Python - you’re free to choose whatever ML tools fit the task best (PyTorch and LightGBM are in production today); ClickHouse, PostgreSQL, Airflow, MLflow, Docker. Requirements: - Experience in predictive modelling and deploying ML models to production: framing an open problem, exploring the data, building baselines, and iterating towards an ML solution; - Strong knowledge of Python and hands-on experience with the modern ML stack; - Profound understanding of statistics and machine learning; - Experience in reinforcement learning, recommender systems, ad tech, or mobile games is a plus; - B2+ level of English; - Fluent Russian is required.
Tech stack: Python - you’re free to choose whatever ML tools fit the task best (PyTorch and LightGBM are in production today); ClickHouse, PostgreSQL, Airflow, MLflow, Docker. Requirements: - Experience in predictive modelling and deploying ML models to production: framing an open problem, exploring the data, building baselines, and iterating towards an ML solution; - Strong knowledge of Python and hands-on experience with the modern ML stack; - Profound understanding of statistics and machine learning; - Experience in reinforcement learning, recommender 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.
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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.
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.
Easybrain is looking for a Data Scientist 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. Your focus will be on building new ML systems for ads monetization and game personalization from the ground up.This is a hands-on, end-to-end role focused on improving business metrics. You will own your models from problem framing through research, production deployment, validation, and post-launch iteration.
Responsibilities:
- Researching and developing ads monetization optimization (floor pricing, ad load balancing) - an open research problem: from studying the underlying dynamics and simple heuristics to ML models and potentially RL;
- Predicting LTV and other key user metrics using large-scale behavioral data: improving forecast accuracy through new modeling approaches, data signals, and features;
- Building in-game personalization systems: difficulty and content management;
- Validating models through A/B tests in collaboration with the analytical team and bringing them to production.
Tech stack: Python - you’re free to choose whatever ML tools fit the task best (PyTorch and LightGBM are in production today); ClickHouse, PostgreSQL, Airflow, MLflow, Docker.
Requirements:
- Experience in predictive modelling and deploying ML models to production: framing an open problem, exploring the data, building baselines, and iterating towards an ML solution;
- Strong knowledge of Python and hands-on experience with the modern ML stack;
- Profound understanding of statistics and machine learning;
- Experience in reinforcement learning, recommender 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.
Data Science
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Limassol
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