Senior Data Scientist / Senior Machine Learning Engineer

Quick Facts

• Role: Senior Data Scientist / Senior Machine Learning Engineer

• Location: Katowice or Warsaw

Description

You will design, build, and evolve end-to-end ML/AI solutions supporting personalization, recommendations, automation, and product decision-making.

You will own the full ML lifecycle—from data analysis and experimentation, through model build/validation, to production deployment, monitoring, and further development. Models will be deployed on Google Cloud using BigQuery and Vertex AI / Gemini Enterprise Agent Platform, including near real-time or real-time scoring.

Responsibilities

• Build and develop ML/AI models and solutions for personalization, recommendations, automation, and product decision-making.

• Run the end-to-end ML lifecycle: data analysis and experiments, model training/validation, production rollout, monitoring, and continued improvement.

• Design end-to-end solutions across data, architecture, integration with other systems, and product/business usage.

• Deploy models to production on Google Cloud using BigQuery and Vertex AI / Gemini Enterprise Agent Platform tools.

• Build and automate ML pipelines for training, scoring, deployment, and monitoring.

• Develop near real-time or real-time solutions (e.g., scoring, recommendations, personalization, decisions based on current user signals).

• Collaborate with Product, CRM, Analytics, and Data Engineering teams to design and implement ML solutions.

Requirements

• Several years of practical experience in Data Science / Machine Learning engineering: building, deploying, and improving solutions.

• Very strong Python and SQL, with working knowledge of large-scale datasets.

• Experience building, validating, and deploying ML models in production environments.

• End-to-end thinking across data, model, architecture, integration, and business application.

• Hands-on knowledge of ML libraries/frameworks: pandas, NumPy, scikit-learn, XGBoost/LightGBM, TensorFlow, or PyTorch.

• Experience with Google Cloud, especially BigQuery and ML/MLOps services from Vertex AI / Gemini Enterprise Agent Platform.

• Practical MLOps: pipelines, model registry, deployment, monitoring, and CI/CD.

• Independence, ownership, and strong communication with both technical and business stakeholders.

Benefits

• Passion- and collaboration-driven team culture.

• Onboarding supported by an assigned partner.

• Modern office in Katowice.

• Free English language classes.

• MedicoverSport card, life insurance, and medical care.

• Free tickets for Poland national team matches.

• Varied, affordable breakfasts and lunches in the company bistro.

• Personal development path and a budget for courses and trainings.

• Fresh fruits daily, good coffee, and healthy snacks.

• Respect for work-life balance.