Senior Machine Learning Engineer (RecSys)

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