Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Machine Learning Engineer

Tripledot Studios
City of London
1 week ago
Create job alert
Overview

The role is within Tripledot's AI group, which works with all studios and engages with Data, Products, and Engineering teams. The AI group aims to make Tripledot an AI-first company. You’ll report to the VP of AI and contribute to main game KPIs such as retention, revenue, player experience, as well as company efficiency and time to market in developing games and features. Progression opportunities exist within the AI group or to studios in the group. The first initiative will be LTV predictions for both Ad-based and IAP-based revenues.

Key Responsibilities
  • Implement cutting-edge ML algorithms for personalization in gaming, staying abreast of the latest advancements and testing what works best for our games and data.
  • Design 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 personalization algorithms and optimise player experience.
  • Continuously monitor and analyse player data to identify new opportunities for personalization and improve existing algorithms.
  • Document work clearly to foster knowledge sharing within the team.
Required Skills, Knowledge and Expertise
  • Bachelor’s degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics) or equivalent experience.
  • Strong understanding of industry-standard ML techniques (e.g., Classification, Regression, Clustering, Recommendation Systems).
  • Experience applying machine learning algorithms to solve real-world problems.
  • Proven experience coding algorithms from research papers into production-ready code (Python preferred).
  • Experience with software development concepts like CI/CD, Version Control, Containers (Docker & Kubernetes) and a proven track record of deploying ML models to production.
  • Proficiency in analytical programming and visualization languages and libraries (SQL, Python and/or R, matplotlib/ggplot, etc.) as well as tools/platforms (e.g., git, SageMaker, VS Code).
  • Strong understanding of statistical concepts (hypothesis testing, sampling, probability distributions).
  • Excellent communication and collaboration skills to bridge technical and non-technical teams.
  • A passion for mobile gaming and a strong desire to create engaging player experiences.
Bonus points if you also have
  • Experience with more complex ML techniques (e.g., Reinforcement Learning).
  • Experience with online A/B testing methodologies in gaming.
  • Experience working in the games industry.
  • Experience deploying real-time ML models.
Working at Tripledot
  • 25 days paid holiday in addition to bank holidays.
  • Hybrid Working: in-office 3 days a week (Tuesdays and Wednesdays) plus a third day of your choice.
  • 20 days fully remote working: work from anywhere in the world, 20 days per year.
  • Daily Free Lunch: £12 daily in-office to order from JustEat.
  • Regular company events and rewards: quarterly on-site and off-site events.
  • Employee Assistance Program: confidential support whenever you need it.
  • Family Forming Support: support on family forming/fertility journey (subject to policy).
  • Life Assurance & Group Income Cover.
  • Continuous Professional Development.
  • Private Medical Cover & Health Cash Plan.
  • Cycle to Work Scheme.
  • Pension Plan.
Seniority level
  • Mid-Senior level
Employment type
  • Full-time
Job function
  • Engineering and Information Technology
  • Industries: Computer Games

Note: This description reflects the responsibilities and requirements for the Senior Machine Learning Engineer role as described. It excludes extraneous job-board listings and unrelated boilerplate.


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Machine Learning Engineer/Computer Vision

Senior Machine Learning Engineer - Robotics

Senior Machine Learning Engineer - Crypto

Senior Machine Learning Engineer - Crypto

Senior Machine Learning Engineer - Crypto

Senior Machine Learning Engineer - Crypto

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How to Write an AI CV that Beats ATS (UK examples)

Writing an AI CV for the UK market is about clarity, credibility, and alignment. Recruiters spend seconds scanning the top third of your CV, while Applicant Tracking Systems (ATS) check for relevant skills & recent impact. Your goal is to make both happy without gimmicks: plain structure, sharp evidence, and links that prove you can ship to production. This guide shows you exactly how to do that. You’ll get a clean CV anatomy, a phrase bank for measurable bullets, GitHub & portfolio tips, and three copy-ready UK examples (junior, mid, research). Paste the structure, replace the details, and tailor to each job ad.

AI Recruitment Trends 2025 (UK): What Job Seekers Must Know About Today’s Hiring Process

Summary: UK AI hiring has shifted from titles & puzzle rounds to skills, portfolios, evals, safety, governance & measurable business impact. This guide explains what’s changed, what to expect in interviews, and how to prepare—especially for LLM application, MLOps/platform, data science, AI product & safety roles. Who this is for: AI/ML engineers, LLM engineers, data scientists, MLOps/platform engineers, AI product managers, applied researchers & safety/governance specialists targeting roles in the UK.

Why AI Careers in the UK Are Becoming More Multidisciplinary

Artificial intelligence is no longer a single-discipline pursuit. In the UK, employers increasingly want talent that can code and communicate, model and manage risk, experiment and empathise. That shift is reshaping job descriptions, training pathways & career progression. AI is touching regulated sectors, sensitive user journeys & public services — so the work now sits at the crossroads of computer science, law, ethics, psychology, linguistics & design. This isn’t a buzzword-driven change. It’s happening because real systems are deployed in the wild where people have rights, needs, habits & constraints. As models move from lab demos to products that diagnose, advise, detect fraud, personalise education or generate media, teams must align performance with accountability, safety & usability. The UK’s maturing AI ecosystem — from startups to FTSE 100s, consultancies, the public sector & universities — is responding by hiring multidisciplinary teams who can anticipate social impact as confidently as they ship features. Below, we unpack the forces behind this change, spotlight five disciplines now fused with AI roles, show what it means for UK job-seekers & employers, and map practical steps to future-proof your CV.