Senior Machine Learning Engineer

Tripledot Studios is a multi-award-winning independent mobile games company with a global team of more than 2,500 people across 12 studios. Its portfolio includes major mobile gaming titles reaching top chart positions worldwide and engaging more than 25 million daily active users.

As a Senior Machine Learning Engineer, you will work on dynamic pricing and recommender-system use cases in Tripledot’s games. The work involves tabular machine learning, including neural networks and gradient-boosted decision trees. You will focus on understanding data, developing features and improving models rather than primarily owning production deployment.

You will work towards defined near-term machine-learning targets, collaborating with the monetisation team and game product teams to plan A/B tests. Over time, you will help translate product and monetisation requirements into machine-learning objectives. In your first three months, you will contribute to the training pipeline and investigate feature and model issues. By around six months, you will be expected to take a more proactive role in setting the direction of the model.

Your responsibilities will include building and improving training pipelines for dynamic-pricing and recommender-system models, covering feature and label design, training, tuning and offline evaluation of tabular models such as neural networks and gradient-boosted trees. You will monitor model performance across live games and products, investigate data and concept drift related to new titles, client versions and user behaviour, and make models easier to extend to other products.

You will diagnose missed model outcomes across the training pipeline, business logic and underlying data, then implement improvements to restore model quality. You will work with monetisation and product colleagues to connect model decisions to revenue and player outcomes, and help plan the A/B tests that inform what ships. As you become established in the team, you will identify gaps in its understanding of the models and propose improvements to their direction.

The role requires hands-on experience training and evaluating tabular models using neural networks or gradient-boosted trees. Relevant experience may include PyTorch, PyTorch Lightning, TensorFlow, XGBoost, CatBoost or scikit-learn; no single framework is required. You should have experience designing features and labels, choosing metrics for model decisions and judging when offline results warrant an A/B test. You will need proficiency in SQL and the ability to write efficient queries to extract, manipulate and aggregate data from relational databases, as well as an investigative approach to incomplete data and requirements that need clarification.

You should be able to explain model results to monetisation and product partners in terms of revenue and player outcomes. Experience in ad tech, recommender systems or online marketplaces would be useful, as would experience with production APIs, deploying machine-learning models or the Ray framework, but none of these is required.

The role uses AI-assisted development tools, including code assistants and LLM-based copilots, to accelerate implementation, debugging and iteration of machine-learning systems while maintaining production-quality standards. You will critically review and validate AI-generated code, model implementations and infrastructure configurations for reliability, correctness and maintainability, and explore AI-powered approaches to improve developer productivity or machine-learning platform capability.

Tripledot offers 25 days’ paid holiday in addition to bank holidays, hybrid working and 20 days of remote working from anywhere in the world, or for covering mandatory office days, each year. Benefits include a daily £12 Just Eat lunch allowance when working in the office, regular on-site and off-site company events, an Employee Assistance Programme, family-forming and fertility support subject to policy, life assurance and group income cover, continuous professional development, optional private medical cover and a health cash plan with Bupa and Medicash, optional dental cover, a Cycle to Work scheme and pension options comprising qualifying earnings or an optional 4% contributory match scheme.