This job has expired and no longer accepts applications.
Warsaw, Poland
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
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
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
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
Expired on: 9/29/2026
GRAI
AI Music Research Lab. AI-powered music platform that’s transforming how people create, explore, and experience music.