Senior Machine Learning Engineer (RecSys)

GRAI; Warszawa; On-site; PLN 100,000 - 130,000; Full time

Benefits offered by this job

Opportunities for growth and learning

Collaborative, product-driven environment

Supportive startup culture

Job summary

GRAI, located in Warsaw, Poland, is seeking a Senior Machine Learning Engineer to design and implement large-scale recommendation systems. In this role, you will work with user interaction data, build end-to-end ML systems, and continuously monitor model performance.

The ideal candidate has strong experience in machine learning, particularly in building recommendation models, and proficiency in Python and relevant frameworks. The role offers the chance to contribute to impactful projects in a dynamic startup environment.

Qualifications

• 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.

Responsibilities

• 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.
• Collaborate with product and engineering teams to align recommendations with business goals.
• Continuously monitor model performance.

Skills

Building recommendation systems

Machine learning fundamentals

Large-scale data management

Python proficiency

ML frameworks (PyTorch, TensorFlow)

Production model deployment

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.

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