Machine Learning Engineering Manager
On-site London Full-time Manager Machine Learning Engineering
At a glance
Manager-level Machine Learning Engineering role at Ravelin Technology. London · full-time · no salary stated · we estimate £60,000–£97,524 across the United Kingdom.
Estimated pay
Ravelin Technology has not published a salary for this role. The figure below is our estimate, not theirs.
£60,000 – £97,524
What the middle half of mid-level machine learning engineering roles in the United Kingdom paid, among postings that did state a salary.
Worked out from 5 postings that stated pay, median £86,000. Last updated Oct 22, 2026.
RoleMachine Learning Engineering
SeniorityManager
LocationLondon
WorkplaceOn-site
EmploymentFull-time
PostedAug 27, 2026 · 8w ago
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Lead and develop machine learning engineers through regular coaching, guidance and people management
- Shape the technical roadmap by advocating for ML methods and tools that support data science experiments
- Work with data engineering, infrastructure and other teams on data architecture and ML product choices
- Investigate underperforming models, then build and deploy fraud detection models while meeting prediction SLAs
- Contribute directly to software or model development as the roadmap calls for it
What you bring
- At least one year managing engineers, including a team of three or more people
- Substantial experience building and deploying machine learning models with Python data tools
- You understand version control, testing, code review and CI/CD practices in an ML engineering setting
- You can spend roughly a third of your time coding and adjust your technical involvement to the roadmap
Who this fits
This manager role suits someone who enjoys developing engineers and collaborating across data science, product, engineering and operations. It combines people leadership with hands-on model and software work. The role is onsite in London.
From the employer
Who are we?
Hi! 👋 We are Ravelin! We're a fraud detection company using advanced machine learning and network analysis technology to solve big problems. Our goal is to make online transactions safer and help our clients feel confident serving their customers.
And we have fun in the meantime! We are a friendly bunch and pride ourselves in having a strong culture and adhering to our values of empathy, ambition, unity and integrity. We really value work/life balance and we embrace a flat hierarchy structure company-wide. Join us and you’ll learn fast about cutting-edge tech and work with some of the brightest and nicest people around - check out our Glassdoor reviews.
If this sounds like your cup of tea, we would love to hear from you! For more information check out our blog to see if you would like to help us prevent crime and protect the world's biggest online businesses.
The Team
You will be joining the Detection team, a team of machine learning engineers and data scientists. The Detection team is responsible for keeping fraud rates low by continuously training and deploying machine learning models. We aim to make model deployments as easy and error-free as code deployments. Google’s Best Practices for ML Engineering is our bible.
Our models are trained to spot multiple types of fraud, using a variety of data sources and techniques in real time. The prediction pipelines are under strict SLAs; every prediction must be returned in under 300ms. When models are not performing as expected, it’s down to the Detection team to investigate why.
The Detection team is core to Ravelin’s success. They work in a deeply collaborative partnership with the Data Engineering team to design the data architecture and infrastructure that powers our ML systems.
The Role
We are currently looking for an Engineering Manager to line manage ML engineers and drive innovation across our suite of fraud detection products. You’ll work closely with data scientists, product, engineering and our operations teams to develop ML models and ML products. Our ideal candidate is pragmatic, approachable and filled with knowledge tempered by past failures.
You will hire, coach and develop a talented machine learning team to deliver on the ML product and platform roadmap. You are in your element working with people. You’ll partner closely with senior members of Detection to discover new avenues for ML product innovation. From time to time, you’re excited to even do some software or model development yourself.
The work is not all green field research. The everyday work is about making safe incremental progress towards better models for our clients. The ideal candidate is willing to get involved in both aspects of the job – and understand why both are important.
Nice to haves
Hi! 👋 We are Ravelin! We're a fraud detection company using advanced machine learning and network analysis technology to solve big problems. Our goal is to make online transactions safer and help our clients feel confident serving their customers.
And we have fun in the meantime! We are a friendly bunch and pride ourselves in having a strong culture and adhering to our values of empathy, ambition, unity and integrity. We really value work/life balance and we embrace a flat hierarchy structure company-wide. Join us and you’ll learn fast about cutting-edge tech and work with some of the brightest and nicest people around - check out our Glassdoor reviews.
If this sounds like your cup of tea, we would love to hear from you! For more information check out our blog to see if you would like to help us prevent crime and protect the world's biggest online businesses.
The Team
You will be joining the Detection team, a team of machine learning engineers and data scientists. The Detection team is responsible for keeping fraud rates low by continuously training and deploying machine learning models. We aim to make model deployments as easy and error-free as code deployments. Google’s Best Practices for ML Engineering is our bible.
Our models are trained to spot multiple types of fraud, using a variety of data sources and techniques in real time. The prediction pipelines are under strict SLAs; every prediction must be returned in under 300ms. When models are not performing as expected, it’s down to the Detection team to investigate why.
The Detection team is core to Ravelin’s success. They work in a deeply collaborative partnership with the Data Engineering team to design the data architecture and infrastructure that powers our ML systems.
The Role
We are currently looking for an Engineering Manager to line manage ML engineers and drive innovation across our suite of fraud detection products. You’ll work closely with data scientists, product, engineering and our operations teams to develop ML models and ML products. Our ideal candidate is pragmatic, approachable and filled with knowledge tempered by past failures.
You will hire, coach and develop a talented machine learning team to deliver on the ML product and platform roadmap. You are in your element working with people. You’ll partner closely with senior members of Detection to discover new avenues for ML product innovation. From time to time, you’re excited to even do some software or model development yourself.
The work is not all green field research. The everyday work is about making safe incremental progress towards better models for our clients. The ideal candidate is willing to get involved in both aspects of the job – and understand why both are important.
- Act as a key leader in establishing excellence within machine learning engineering and across the detection team
- Line manage a team of machine learning engineers - providing coaching and guidance in support of the ongoing development and growth of your team
- Propose and champion new machine learning methods and tools (including platforms that empower Data Science experimentation) to influence the technical roadmap and promote continuous innovation
- Drive cross-functional initiatives with Data Engineering, Infra, and other teams to align on data architecture and ensure we make the right ML product decisions
- Investigate model performance issues
- Develop and deploy new models to detect fraud whilst maintaining SLAs
- Minimum of 1 year of experience as an engineering manager, managing at least 3 people
- You are a strong collaborator with colleagues outside of your immediate team, for example with data science, engineering, product, client operations teams and with senior leadership
- You know how to manage and retain talented engineers from a diverse range of backgrounds and personalities. You can handle difficult management situations with tact, empathy and support
- You have significant experience building and deploying ML models using the Python data stack
- Familiarity with modern workflow orchestration tools such as Prefect, Kubeflow, Argo, etc.
- You understand software engineering best practices (version control, unit tests, code reviews, CI/CD) and how they apply to machine learning engineering
- Comfortable spending 30-40% of your time hands-on in the codebase and adapting your technical involvement based on the roadmap
Nice to haves
- Pytorch or Tensorflow deep learning experience
- Experience with Go, C++, Java or another systems language
- Experience using dbt