ML Engineer

Responsibilities

• Design, develop, and deploy end-to-end ML systems and pipelines in a production environment.
• Research and identify algorithms that best fit specific business and technical problems.
• Collect, clean, prepare, verify, and perform feature engineering for model training.
• Deploy models, build monitoring systems for performance and data drift detection, and automate model retraining processes
• Run A/B tests, optimize model efficiency and inference speed.
• Work closely with Data Analysts, Data Engineers, and Developers to ensure seamless integration of ML solutions into the product ecosystem.
• Stay up to date with the latest ML algorithms, frameworks, and tools, applying them where beneficial.

Requirements

• 3+ years of experience in applied Machine Learning or Data Science.
• Ability to work independently and take ownership of projects from idea to production.
• Strong programming skills in Python and proficiency with key ML libraries.
• Solid understanding of statistical modeling, feature engineering, and data preprocessing.
• Hands-on experience deploying and maintaining ML models in production.
• Experience with ETL processes and data pipelines.
• Strong knowledge of SQL and working with large datasets.
• Understanding of MLOps principles (model lifecycle, monitoring, retraining).
• Familiarity with cloud environments (AWS, GCP, or Azure) is a plus.
• English level: Intermediate+ for documentation and team communication

Tech Stack
Core:
Python, Scikit-learn, pandas, CatBoost, LightGBM/XGBoost, SQL

Nice to have:
Airflow, MLflow, Docker, Spark

Bonus:
Experience building anti-fraud or spam detection systems

We offer

• Official employment and support for a work visa
• Opportunities for professional growth
• Friendly work environment
• Flexible start to the workday