Machine Learning Engineer

About the role

You will work with senior engineers on internal classical machine learning initiatives, combining structured learning, practical delivery, and gradual ownership of increasingly complex tasks.

Key responsibilities

• Prepare and validate structured datasets for ML tasks, including cleaning, transformation, encoding, scaling, and handling missing values.
• Conduct exploratory data analysis to identify patterns, data quality issues, and modeling opportunities.
• Build, test, and compare ML models for regression, classification, clustering, dimensionality reduction, and anomaly detection.
• Develop and select features under guidance, run experiments, tune parameters, and evaluate results using appropriate validation approaches.
• Maintain reproducible ML pipelines, notebooks, experiment tracking, and technical documentation.
• Write and maintain automated tests for data and model code and support model delivery via REST APIs or batch workflows.

Required profile

• 1+ year of hands‑on Python development experience with pandas, NumPy, scikit‑learn, and Jupyter.
• Strong foundation in statistics, probability, linear algebra, and exploratory data analysis.
• Understanding of supervised and unsupervised learning, model evaluation, cross‑validation, and regularization.
• SQL skills for data extraction and analysis.
• Ability to explain model behavior, assumptions, limitations, and results.
• English proficiency at B2 level or higher.

Required skills

• Python
• pandas
• NumPy
• scikit‑learn
• Jupyter
• SQL
• XGBoost
• LightGBM
• MLflow
• FastAPI
• Git
• Docker
• pytest

What we offer

• Technical and non‑technical training for professional and personal growth.
• Internal conferences and meetups with industry experts.
• Mentorship and support from experienced employees.
• Health insurance and sports activities.
• Flexible work options, including remote and hybrid opportunities.
• Referral program, work anniversary program, and additional vacation days.