Data Scientist, Recommender Systems | Remote | Python, PyTorch, Deep LearningMillions of players. Thousands of games. One question: what should they play next?We're hiring a Data Scientist specialising in Recommender Systems for a fast-growing integral gaming technology company. You'll build the machine-learning models that decide what millions of players discover, and you'll see your work go live, not sit in a notebook.
What you'll actually doBuild recommendation models. Candidate generation, retrieval and ranking that make every player's lobby feel personal.
Predict what's next. Use sequential behaviour, user and item embeddings and deep learning for next-item prediction.
Ship to production. Take models from data and experiments through deployment and monitoring, then keep improving them.
Prove it works. Run offline evaluation and A/B testing, and connect model quality to real product results.
Try new things. Test transformer-based recommendation, two-tower models and multimodal signals where they genuinely help.




What you'll bringAround 3–5 years of hands-on experience in machine learning, with real work on recommender systems, personalisation or rankingStrong Python and SQLDeep-learning experience with PyTorch, TensorFlow or JAXModels you've taken to production on AWS, GCP or AzureThe ability to explain what you built, why, and what changed because of itTwo-tower models, learning to rank, ANN search, cold start, session-based recommendations, MLOps, Spark, Kafka or Flink. Experience from e-commerce, streaming, media, marketplaces or ad tech counts. Your job title matters less than what you've built.
Why you'll like itReal scale: your models reach millions of players worldwide.
Real ownership: you own problems from idea to production.
Real growth: learn alongside data scientists, ML engineers and data engineers who ship.
Modern stack: deep learning, cloud ML and real-time data, with room to test new ideas.

📌 Data Scientist Recommender Systems (Valencia)
🏢 EyeSpy Recruitment
📍 Valencia