ML Engineer

ML Engineer

Location: Remote / Poland Rate: Up to 140 PLN/h English: B2+ Start date: 30 November 2026 Contract duration: 12 months

About the project

We are looking for an experienced ML Engineer to join a project focused on developing and deploying machine learning solutions that drive business decisions and marketing performance.

You will be responsible for building production-ready ML models, integrating predictions with external platforms, and developing scalable data and ML workflows in Google Cloud Platform (GCP).

The role combines hands-on machine learning engineering, data processing, cloud infrastructure, and business-oriented model optimization.

Requirements - Must have

• 5+ years of hands-on experience in Python-based Machine Learning Engineering, including ownership of deployed models and writing reliable production-grade code.
• Proven experience integrating ML predictions with external platforms via APIs to enable automated actions such as campaign optimization, recommendations, or pricing decisions.
• Advanced SQL and BigQuery skills, particularly in feature engineering, data validation, and recurring data transformations.
• Practical experience deploying ML workloads on GCP, including services such as Vertex AI, Pub/Sub, Cloud Run, and Composer/Airflow.
• Production experience with gradient-boosting algorithms such as LightGBM, CatBoost, or XGBoost, including model tuning and evaluation using business-relevant metrics.
• Understanding of prediction calibration and the ability to assess how model errors impact downstream business decisions.

Strongly preferred

• Experience with entity matching or identity resolution, connecting customer records and events across multiple systems.
• Previous experience with purchase propensity, customer retention, segmentation, or Customer Lifetime Value (CLV/LTV) models, preferably in e-commerce or DTC environments.
• Experience delivering server-side conversion signals to advertising platforms such as Google Ads or Meta.
• Knowledge of Bayesian methods and probabilistic customer models, including BG/NBD and Gamma-Gamma.

Nice to have

• Experience with experimentation, causal inference, or multi-armed bandit methods applied to marketing investment optimization.
• Familiarity with Docker, Terraform, and automated CI/CD pipelines.
• Experience using AI-powered coding assistants such as Cursor or Claude Code.