# Senior Machine Learning Engineer \(RecSys\) - Company: [Grai]() - Location: Warsaw, Poland - Remote: Yes - Team: R&D - Employment type: Full Time - Posted: June 9, 2026 ## Job description We are building an AI-powered music platform that’s transforming how people create, explore, and experience music. Our product leverages cutting-edge AI technologies to provide personalized music recommendations and unique features tailored to every music enthusiast. As we continue to grow, we’re looking for a **Senior Machine Learning Engineer** to design, build, and scale recommendation systems that deliver highly relevant, personalized experiences to our users. You will work on large-scale user interaction data, develop retrieval and ranking models, and take them from experimentation to production. ## **What You’ll Do** * Design and implement retrieval and ranking architectures for personalized recommendations * Work with large-scale user behavior and content data to extract meaningful signals * Build end-to-end ML systems: data processing, feature engineering, training, evaluation, deployment, monitoring * Run A/B tests and offline evaluations to measure model impact and guide improvements * Collaborate with product and engineering teams to align recommendations with business goals * Continuously monitor model performance ## **What We’re Looking For** * Strong hands-on experience building recommendation systems or ranking models * Deep understanding of machine learning fundamentals and evaluation methodologies * Experience working with large-scale data (SQL, Spark, or distributed data systems) * Proficiency in Python and modern ML frameworks (PyTorch, TensorFlow) * Understanding of core ML concepts: supervised/unsupervised learning, evaluation metrics, feature engineering * Experience deploying ML models to production and maintaining them over time * Ability to balance experimentation with production reliability ## **Nice to Have** * Experience with real-time recommendation systems * Knowledge of search / information retrieval systems * Familiarity with feature stores, model monitoring, and ML infrastructure * Experience in media, music, or consumer-facing personalization products ## **Why Join Us** * Work on high-impact ML systems used by real users at scale * Ownership over meaningful technical decisions, from modeling to production * Collaborative, product-driven environment with strong engineering culture * A supportive and dynamic startup culture where your ideas and contributions truly matter * Opportunities for growth, learning, and shaping the future of our recommendation stack ## Apply [Apply on Grai]() Canonical job page: