Tripledot Studios
Senior Machine Learning Engineer

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Who are we?
Tripledot Studios is one of the largest independent mobile games companies in the world. We are a multi-award-winning organisation, with a global 2,500+ strong team across 12 studios. Our expanded portfolio includes some of the biggest titles in mobile gaming, collectively reaching top chart positions around the world and engaging over 25 million daily active users.
Tripledot’s guiding principle is that when people love what they do, what they do will be loved by others. We’re building a company we’re proud of. One filled with driven, incredibly smart and detail-orientated people, who LOVE making games.
Our ambition is to be the most successful games company in the world, and we’re just getting started.
The role is working within our AI group
The group AI team is a central function that works both with other central groups like marketing and game solutions and the game studios which are part of Tripledot. Within the group AI team, you’ll be working with other AI/ ML Eng, Data engineers, analysts, and product owners.
Role Overview
Within the various studios and other central teams, you will interact with data, engineering, and product teams. The role will be directly contributing to main games KPIs such as retention, revenue, player experience, as well as to company efficiency and time to market in developing games and features. Progression opportunities will be within the AI group or to studios in the group.
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I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
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Graduate Consultant — 2026 Scheme
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Key Responsibilities
- Implement cutting-edge ML algorithms for personalization in gaming, staying abreast of the latest advancements in the field, and testing to see what works best for our games and data.
- Designing experiments and prototypes to test the viability and efficiency of new AI models.
- Translate research findings into real-world applications by creating algorithm prototypes in our codebase.
- Convert prototypes into production level code that can be easily managed and deployed through the ML Lifecycle.
- Design, develop, and evaluate A/B tests to measure the effectiveness of personalisation algorithms and optimise player experience.
- Continuously monitor and analyse player data to identify new opportunities for personalisation and improve existing algorithms.
- Document your work clearly and concisely, fostering knowledge sharing within the team.
What we’re looking for
- A Bachelor's degree or higher in a quantitative field (e.g., computer science, mathematics, statistics), another quantitative applied field or equivalent experience.
- Strong understanding of industry standard ML techniques (from classification to reinforcement learning and generative methods)
- Experience in applying machine learning algorithms to solve real-world problems.
- Experience with software development concepts like CI/CD, Version Control, Containers (Docker & Kubernetes) and proven track record of deploying ML models to production and established MLOps concepts.
- A good command of analytical programming and visualisation languages and libraries (SQL, python, matplotlib, etc.) as well as some of the supporting tools and platforms (e.g. git, MLFlow, Kubernetes, Kubeflow, Trino, AirFlow).
- A strong understanding of statistical concepts (hypothesis testing, sampling, probability distributions).
- Excellent communication and collaboration skills to effectively bridge the gap between technical and non-technical teams.
- Experience with using generative AI copilots or agents in daily development work.
- A passion for mobile gaming and a strong desire to create engaging player experiences and drive business results.


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Bonus points if you also have:
- Experience with more complex ML techniques (e.g. Reinforcement Learning).
- Experience with A/B testing methodologies in an online gaming context.
- Experience working in the games industry.
Working at Tripledot
- Time Off: Statutory Time Off policy for location in addition to bank holidays to relax and refresh throughout the year.
- Health & Wellness: Based on country requirements. Private Healthcare or Healthcare stipend subject to eligibility.
- Continuous Professional Development: Propel your career with continuous opportunities for professional development.
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