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ML Engineer
Компания: co.brick Talents
Город: Gliwice
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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.