Senior MLOps and Machine Learning Engineer in London

Senior MLOps and Machine Learning Engineer in London

London Full-Time 63000 - 77000 £ / year (est.) Hybrid
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At a Glance

  • Tasks: Build and improve machine learning models for dynamic pricing and recommendations in mobile games.
  • Company: Join Tripledot Studios, a leading independent mobile games company with a global team.
  • Benefits: Enjoy 25 days holiday, hybrid working, free lunch, and continuous professional development.
  • Other info: Dynamic work environment with opportunities for career growth and exciting company events.
  • Why this job: Make an impact in the gaming industry with cutting-edge ML technology and innovative projects.
  • Qualifications: Experience with tabular models, SQL proficiency, and a passion for data-driven decision making.

The predicted salary is between 63000 - 77000 £ per year.

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. We’re building a company we’re proud of, 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.

Role Overview

Join Tripledot Studios as a Senior Machine Learning Engineer working on dynamic pricing and recommender systems use cases in our games. The work involves tabular machine learning, including neural networks and approaches such as gradient-boosted decision trees. You'll focus on understanding the data, developing features and improving the models, rather than primarily owning production deployment. You'll work toward defined near-term ML targets, collaborating with the monetization team and game product teams to plan A/B tests. Over the longer term, you'll work with those teams to translate product and monetization requirements into ML objectives. You'll start by learning the project and its business goals. Within the first three months, we'd expect you to contribute to the training pipeline and investigate features and model issues.

Key Responsibilities

  • Build and improve training pipelines for dynamic pricing and recommender system models, from feature and label design through training, tuning and offline evaluation of tabular models such as neural networks and gradient-boosted trees.
  • Monitor model performance once models are live across games and products. Investigate data and concept drift, including shifts tied to new titles, client versions or user behaviour, and make models easier to extend to another product.
  • Diagnose missed model outcomes across the training pipeline, business logic and underlying data, then work through the improvements needed to restore model quality.
  • Work with monetization and product colleagues to connect model decisions to revenue and player outcomes, and help plan the A/B tests that inform what ships.

Required Skills, Knowledge and Expertise

  • Hands-on training and evaluation of tabular models, using neural networks or gradient-boosted trees.
  • Proficiency in SQL and the ability to write efficient queries to extract, manipulate and aggregate data from relational databases.
  • An investigative approach to incomplete data and longer-term requirements that need clarification.
  • Experience in ad tech, recommender systems or online marketplaces would be useful, as would experience with production APIs or deploying ML models.
  • 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.
  • Critically reviews and validates AI-generated code, model implementations and infrastructure configurations for reliability, correctness and maintainability, and explores AI-powered approaches to improve developer productivity or ML platform capability.

Working for Tripledot

  • 25 days paid holiday in addition to bank holidays to relax and refresh throughout the year.
  • Hybrid Working: 20 days remote working: Work from anywhere in the world, or use the time to cover mandatory office days to WFH, 20 days of the year.
  • Daily Free Lunch: when in the office you get £12 every day to order from JustEat.
  • Regular company events and rewards: quarterly on-site and off-site events that celebrate cultural events, our achievements and our team spirit.
  • Employee Assistance Program: Anytime you need it, tap into confidential, caring support with our Employee Assistance Program, always here to lend an ear and a helping hand.
  • Receive vital support on your family forming/ fertility journey with our support program [subject to policy].
  • Life Assurance & Group Income Cover: Financial protection for you and your loved ones.
  • Continuous Professional Development: Propel your career with continuous opportunities for professional development.
  • Private Medical Cover & Health Cash Plan: Opt-in (P11d benefit) comprehensive private medical cover with Bupa and cash plan with Medicash.
  • Dental Cover: Opt-in (P11d benefit).
  • Cycle to Work Scheme: Salary sacrifice bike purchase scheme.
  • Pension Plan: Qualifying earnings or opt-in 4% contributory match schemes offered.

Senior MLOps and Machine Learning Engineer in London employer: Tripledot Studios

Tripledot Studios is an exceptional employer, offering a vibrant work culture that thrives on creativity and innovation in the mobile gaming industry. With a strong emphasis on employee growth, the company provides continuous professional development opportunities, hybrid working arrangements, and generous benefits such as 25 days of paid holiday, daily free lunches, and comprehensive health coverage. Located in San Francisco, employees enjoy a dynamic environment where they can collaborate with talented individuals and contribute to the success of award-winning games that engage millions worldwide.

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Contact Details:

Tripledot Studios Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior MLOps and Machine Learning Engineer in London

✨Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Tripledot Studios or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

✨Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Tripledot Studios.

✨Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Tripledot Studios.

✨Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Tripledot Studios that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace Senior MLOps and Machine Learning Engineer in London

Machine Learning
Tabular Models
Neural Networks
Gradient-Boosted Decision Trees
SQL
Data Manipulation
A/B Testing

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Tripledot Studios.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Tripledot Studios and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Tripledot Studios

✨Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

✨Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Tripledot Studios uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

✨Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

✨Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.