Data Engineer + ML - Hybrid (Warsaw)

O projekcie: Correct Context is looking for a Data Engineer + ML for Samba TV in Warsaw, Poland. Samba TV tracks streaming and broadcast video across the world with our proprietary data and technology. We are on a mission to fundamentally transform the viewing experience for everyone. Our data enables media companies to connect with audiences for new shows and movies, and enables advertisers to engage viewers and measure reach across all their devices. We have an amazing story with a unique perspective on culture formed by a global footprint of data and AI-driven insights. We offer: - Real big data projects 🚀  - An international team (US, PL, GB) 🌎  - A small, independent team working environment 🧑‍💻  - High influence on working environment 🎯  - A hands-on environment with real ownership 🛠️  - Hybrid work model in Warsaw, Poland (3 days in the office / 2 days from home) 🏢  - 15,000 - 28,000 PLN net/month B2B 💰  - Free lunch in the office 🍽️  If you don't have all the qualifications, but you think there is a match, let's talk! The recruitment process for theData Engineer + ML position has following steps: - Technical survey ~ 10min  - Technical screening - 30 min  - Technical Interviews with Samba TV team members - 3 or 4 interviews of around 60 min each Wymagania: The candidate must have: - 2+ years of hands-on ML experience  - Advanced Python, strong SQL, and PySpark experience for large-scale datasets  - Databricks workflows, Delta Lake  - AWS or GCP experience  - Ability to document technical decisions clearly  Nice to have: - RAG systems, LLM-augmented models, vector databases, or semantic search experience  - Knowledge graph construction, entity resolution, or semantic data modeling exposure  - Media, ad tech, or measurement background  - Master's degree in a quantitative field Codzienne zadania: - Own end-to-end delivery of significant data science projects, from problem scoping and approach design through to production deployment  - Build production-quality Python and PySpark solutions on Databricks for ML and AI-powered workflows  - Develop reusable tools, libraries, and documentation that improve team efficiency and technical standards  - Mentor team members and help raise the bar for code quality and technical execution  - Collaborate closely with Product, Engineering, and Operations on scalable, production-ready solutions