Senior Machine Learning Engineer

Overview

As a Senior Machine Learning Engineer at Tripledot Studios, you will shape dynamic pricing and recommender systems for our global mobile games. You’ll build and refine tabular ML models, collaborating with monetization and product teams to link model decisions to revenue and user outcomes. The role focuses on data understanding, feature engineering, and model improvement with less emphasis on production deployment. You’ll contribute to training pipelines, monitor model health, and guide model direction over time, enabling ambitious growth in our games portfolio. This is a hands-on role that blends ML with business impact in a fast-paced, cross-functional environment.

Pay / Benefits

• 25 days holiday
• Hybrid Working
• Daily free lunch
• Employee Assistance Program
• Private medical cover
• Pension plan

Responsibilities

• Build and improve training pipelines for dynamic pricing and recommender system models (tabular models, neural networks, gradient-boosted trees)
• Monitor live model performance across games and products; address data shifts and drift
• Diagnose and remediate issues in the training pipeline, business logic, and data to restore model quality
• Collaborate with monetization and product teams to tie model decisions to revenue and player outcomes and plan A/B tests
• Identify knowledge gaps in the team and propose improvements to model direction
• Gradually take a proactive role in setting the model’s direction as you ramp up

Key requirements

• Hands-on training and evaluation of tabular models using neural networks or gradient-boosted trees
• Experience with PyTorch, PyTorch Lightning, TensorFlow, XGBoost, CatBoost or scikit-learn (any one/framework)
• Feature and label design, selecting metrics, and determining when to run offline vs. A/B tests
• Proficiency in SQL and writing efficient queries for relational data
• Investigative mindset for dealing with incomplete data and longer-term requirements
• Ability to communicate model results to monetization and product partners in business terms
• Experience in ad tech, recommender systems or online marketplaces; experience with production APIs or deploying ML models is a plus
• Familiarity with Ray is a plus
• Use of AI-assisted development tools and critical review of AI-generated code and configurations

• Collaborative cross-functional communication
• Analytical and problem-solving mindset
• Proactive and initiative-taking attitude
• Tabular ML modeling (neural nets, gradient-boosted trees)
• PyTorch, PyTorch Lightning, TensorFlow, XGBoost, CatBoost or scikit-learn
• SQL and relational data manipulation

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