Machine Learning Engineer

Machine Learning Engineer

Our advertising network handles 10+ billion events daily across 500 servers in 5 data centers (Europe & the US). We process over 1 million requests per second at peak load, and our ClickHouse cluster stores more than 3.6 petabytes of data. And yet, everything works like Swiss clockwork — thanks to our team of smart, talented, and proactive individuals.

We’re looking for an ML Engineer to productionize machine learning models on massive real-time and historical data, tackling problems such as predictive scoring, user and behavioral modeling, anomaly and abuse detection, and recommendation/ranking under strict latency constraints.

Responsibilities:

• Develop, evaluate, and improve machine learning models to drive product performance and business outcomes
• Conduct deep exploratory analysis of product and user data (hundreds of billions of events per month)
• Build predictive and classification models to support decision-making and optimization
• Design, deploy, and maintain production ML services (model training, serving, monitoring, automated retraining)
• Contribute to ML system design by building pipelines, defining data, metrics, and features
• Collaborate closely with analysts, developers, product managers, and other team members
• Participate in feature selection, A/B test design, and model validation
• Identify growth opportunities and optimization areas in traffic and user behavior
• Develop internal tools and dashboards to monitor key product and model metrics
• Ensure data quality and build pipelines for monitoring and anomaly detection
• Clearly communicate hypotheses, results, and insights to both technical and non-technical stakeholders
• Drive continuous improvement of ML systems, models, and analytical processes

Requirements:

• 3+ years of experience in machine learning, data science, or applied ML
• Experience in machine learning systems design — from problem formulation to building APIs for production integration
• Strong background in statistics, hypothesis testing, and experimental design
• Proficiency in SQL (experience with ClickHouse is a strong plus)
• Experience working with large-scale datasets (terabytes to petabytes)
• Strong programming skills in Python or R for data analysis and ML (pandas, scikit-learn, XGBoost, LightGBM, etc.)
• Ability to build, evaluate, and interpret regression, classification, and clustering models
• Experience with BI and visualization tools (Grafana, Tableau, Power BI, etc.)
• Proactive, curious, and results-oriented mindset
• Ability to clearly explain technical concepts to non-technical stakeholders
• Strong problem-solving skills and ability to decompose complex problems

Will be a plus:

• Hands-on experience with production ML systems, model lifecycle management, or MLOps practices

We Offer:

• No dress code, no bureaucracy
• Fully official employment with a competitive salary above market level
• Laptop of your choice: Mac or PC
• Medical insurance and mobile communication
• Free lunches, beverages, fresh fruit, and snacks in the office
• Free English course
• Gym membership coverage and fitness reimbursement
• Partial compensation for schools and childcare (50%)