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Senior Machine Learning Engineer (RecSys)

GRAI Inc. Warsaw, Mazowieckie, Poland

Jun 09
Remote machine-learning Senior (5-10 yrs) Full-time Poland
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About the role

Design and implement retrieval and ranking architectures for personalized music recommendations. Build end-to-end ML systems encompassing data processing, training, deployment, and continuous performance monitoring.

What they look for

Recommendation Systems Ranking Models Python PyTorch TensorFlow SQL Spark Distributed Data Systems Feature Engineering A/B Testing MLOps Information Retrieval Supervised Learning Unsupervised Learning Model Monitoring Data Processing

Requirements

Requires strong hands-on experience with recommendation systems, ranking models, and large-scale data processing using Python and modern ML frameworks. Candidates should be proficient in deploying and maintaining production-level ML models.

Full 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

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