Senior Machine Learning Engineer

Ravelin; London; Hybrid; GBP 70,000 - 110,000; Full time

Job summary

Join a leading fraud detection company as a Senior Machine Learning Engineer. In this role, you'll shape the architectural direction of high-performance ML systems while collaborating closely with data engineers and scientists. This position offers a chance to impact fraud detection at scale, backed by a commitment to technical excellence and innovative methodologies.

Benefits

Flexible Working Hours & Remote-First Environment

Comprehensive BUPA Health Insurance

£1,000 Annual Wellness and Learning Budget

Monthly Wellbeing and Learning Day

25 Days Holiday + Bank Holidays + 1 Extra Cultural Day

Mental Health Support via Spill

Aviva Pension Scheme

Fortnightly Randomised Team Lunches

Qualifications

• Experience in designing complex ML systems and production deployment.
• Deep understanding of machine learning lifecycle.
• Ability to lead cross-functional projects.

Responsibilities

• Lead design and architecture of scalable end-to-end ML pipelines.
• Drive initiatives to align on data architecture with other teams.
• Mentor team members and foster technical excellence.

Skills

Problem-Solving

Collaboration

Communication

Education

Degree in Computer Science or similar

Tools

Prefect

Kubeflow

Argo

PyTorch

TensorFlow

Spark

Job description

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 data scientists and machine learning engineers. The Detection team is responsible for keeping fraud rates low – and clients happy – 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 looking for a Senior Machine Learning Engineer to join our Detection team. In this role, you will be setting the technical direction that bridges data science and engineering. You will be responsible for the architecture, scalability, and reliability of the high-performance ML systems that form the core of our fraud detection platform. Beyond just consuming data, you will take a leading role in defining how data is modeled, stored, and served for machine learning purposes, directly influencing the architecture of our feature generation pipelines and ensuring data quality throughout the ML lifecycle.

You'll take strategic ownership over several aspects of our ML infrastructure and be empowered to introduce and champion new ideas that shape the future of our processes and tools. Your day-to-day will involve close collaboration with engineers and data scientists to operate machine learning at scale, while also providing mentorship and guidance to other members of the team.

Responsibilities

• Lead the design, architecture, and orchestration of scalable and reliable end-to-end ML pipelines – from raw data extraction and feature engineering to model training and inference – with a focus on handling terabyte-scale datasets efficiently.
• Propose and champion new machine learning methods and tools to influence the technical roadmap and drive continuous innovation.
• Drive cross-functional initiatives with Data Engineering, Infra, and other teams to align on data architecture and ensure our ML systems meet overarching business objectives.
• Evolve our MLOps infrastructure, driving the strategy for model versioning, automated deployments, monitoring, and observability using modern tools like Prefect.
• Mentor and guide other members of the team, fostering a culture of technical excellence and continuous improvement through code reviews, design discussions, and knowledge sharing.
• Lead technical deep-dives to troubleshoot and resolve performance bottlenecks and availability issues in our ML systems.
• Champion and contribute to the continuous improvement of our internal tools and engineering best practices.

Requirements

• Demonstrable experience designing, building, and deploying complex machine learning systems in a production environment.
• Deep understanding of the full machine learning lifecycle, from research to deployment and a track record of leading the design and implementation of scalable training pipelines for large datasets.
• Working experience leading complex, cross-functional projects and influencing technical direction across multiple teams.
• Familiarity with modern workflow orchestration tools such as Prefect, Kubeflow, Argo, etc.
• Software engineering fundamentals, including data structures, design patterns, version control (Git), CI/CD, testing, and monitoring.
• Exceptional problem-solving skills, with a proven ability to navigate ambiguity and lead technical deep-dives to resolve complex issues.
• A collaborative mindset and strong communication skills with the ability to communicate to a range of audiences.

Nice to Haves

• Proficiency in a systems programming language (e.g., Go, C++, Java, Rust).
• Experience with deep learning frameworks like PyTorch or TensorFlow.
• Experience with large-scale data processing engines like Spark and Dataproc.
• Familiarity with data pipeline tools like dbt.

Benefits

• Flexible Working Hours & Remote-First Environment — Work when and where you’re most productive, with flexibility and support.
• Comprehensive BUPA Health Insurance — Stay covered with top-tier medical care for your peace of mind.
• £1,000 Annual Wellness and Learning Budget — Prioritise your health, well-being and learning needs with funds for fitness, mental health, and more.
• Monthly Wellbeing and Learning Day — Take every last Friday of the month off to recharge or learn something new, up to you.
• 25 Days Holiday + Bank Holidays + 1 Extra Cultural Day — Enjoy generous time off to rest, travel, or celebrate what matters to you.
• Mental Health Support via Spill — Access professional mental health services when you need them.
• Aviva Pension Scheme — Plan for the future with our pension program.
• Ravelin Gives Back — Join monthly charitable donations and volunteer opportunities to make a positive impact.
• Fortnightly Randomised Team Lunches — Connect with teammates from across the company over in person or remote lunches every other week, on us!
• Cycle-to-Work Scheme — Save on commuting costs while staying active.
• BorrowMyDoggy Access — Love dogs? Spend time with a furry friend through this unique perk.
• Weekly Board Game Nights & Social Budget — Unwind with weekly board games or plan your own socials, supported by a company budget.

*Job offers may be withdrawn if candidates do not meet our pre-employment checks: unspent criminal convictions, employment verification, and right to work*