Senior ML Engineer - Dynamic Pricing & Recommender Systems

Tripledot Studios Limited; Barcelona; Híbrido; EUR 60.000 - 90.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

25 days holiday

Hybrid working (20 remote days)

Private medical cover

Life & Critical illness cover

Employee assistance program

Sport compensation

Meal & transport vouchers

English & Spanish classes

Continuous professional development

Descripción de la vacante

Tripledot Studios Limited is seeking a Senior Machine Learning Engineer to work on dynamic pricing and recommender systems in our mobile gaming platform. You will build training pipelines, experiment with tabular models, and collaborate with monetization and product teams to drive revenue outcomes.

The role emphasizes understanding data, feature engineering, and evolving model direction over time, with a hybrid work setup and global collaboration.

Formación

• Hands-on training and evaluation of tabular models.
• Experience designing features and labels and selecting metrics for model decisions.
• Proficiency in SQL and writing efficient data queries.
• Ability to explain model results to business partners.

Responsabilidades

• Build and improve training pipelines for dynamic pricing and recommender models.
• Monitor model performance across games and products and investigate data and drift.
• Diagnose missed outcomes in the training pipeline and implement fixes.
• Collaborate with monetization and product teams to link model decisions to revenue and player outcomes.
• Identify gaps in team understanding and propose improvements.

Conocimientos

Tabular models

Model training

SQL proficiency

Model explainability

Recommender systems

Ad tech experience

Ray framework

AI-assisted tools

Herramientas

PyTorch

PyTorch Lightning

TensorFlow

XGBoost

CatBoost

scikit-learn

Descripción del empleo

Tripledot Studios Limited is seeking a Senior Machine Learning Engineer to work on dynamic pricing and recommender systems in our mobile gaming platform. You will build training pipelines, experiment with tabular models, and collaborate with monetization and product teams to drive revenue outcomes.

The role emphasizes understanding data, feature engineering, and evolving model direction over time, with a hybrid work setup and global collaboration.