Machine Learning Engineer

The Change Partners - Global talent specialists for a connected world
London
1 day ago
Create job alert

Permanent

Hybrid Working


The Change Partners are working with a global leader in the travel software space to find looking for an ML Engineer to join their Marketing Measurement Analytics team. This is a high-impact role where your code directly influences how brands like global booking platforms allocate investment and drive growth.


You’ll be embedded in the core team responsible for driving global consumer growth. Your job is to solve a complex puzzle: how do we quantify success at scale? You will balance your time between stabilising a high-traffic experimentation platform and innovating on new, flexible measurement frameworks.


Your Responsibilities:


  • Scale Experimentation: Support engineering teams in maintaining a platform that runs 300+ experiments a year. You’ll troubleshoot performance, enhance logging, and ensure the system never blinks.
  • Optimise Core Logic: Fine-tune the "math under the hood," including stratified sampling, simulations, and regression frameworks.
  • Bridge the Gap: Take raw research prototypes and transform them into robust, production-grade code libraries that other teams can actually use.
  • Build Data Pipelines: Design and deploy scalable pipelines using PySpark to handle massive datasets for experiment execution.
  • Collaborate: Work cross-functionally with Data Scientists and Software Engineers to turn complex requirements into seamless deployments.


What We’re Looking for:


  • You have a degree in CS, Math, or Engineering, Data Science3
  • Expert with Python, SQL, and PySpark.
  • 3+ years in a similar role with a globally recognised large brand
  • Production Experience: You’ve built and shipped scalable systems before (ideally with ML/AI components)
  • DevOps Mindset: You’re comfortable with version control, unit testing, and automated deployment pipelines (GitHub Actions).
  • You built reusable frameworks and modular code that lasts.
  • Bonus Points: If you’ve worked with AWS/GCP, understand the nuances of A/B testing, or have a passion for open-source development, we definitely want to talk.


Please note this role doesn’t offer sponsorship. Please apply to learn more about the role.

Related Jobs

View all jobs

Machine Learning Engineer Python AWS

Machine Learning Engineer Python AWS

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

Machine Learning Engineer

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 Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.