Senior Machine Learning EngineerRavelin Technology • London, England, United Kingdom
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Senior Machine Learning Engineer
Ravelin Technology
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- +1
- London, England, United Kingdom
- +3
- +1
- London, England, United Kingdom
About
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 Have
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 — Top-tier medical care for your peace of mind
£1,000 Annual Wellness and Learning Budget — Funds for fitness, mental health, and learning needs
Monthly Wellbeing and Learning Day — Take every last Friday of the month off to recharge or learn something new
25 Days Holiday + Bank Holidays + 1 Extra Cultural Day — Generous time off to rest, travel, or celebrate
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 — Monthly charitable donations and volunteer opportunities
Fortnightly Randomised Team Lunches — In-person or remote lunches every other week
Cycle-to-Work Scheme — Save on commuting costs while staying active
BorrowMyDoggy Access — Spend time with a dog through this perk
Weekly Board Game Nights & Social Budget — Unwind with board games or socials
Pre-employment checks notice — Job offers may be withdrawn if candidates do not meet our pre-employment checks: unspent criminal convictions, employment verification, and right to work
Industries
IT Services and IT Consulting
Seniority Level
Mid-Senior level
Employment Type
Full-time
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Nice-to-have skills
- Machine Learning
Work experience
- Data Engineer
- Machine Learning
- DevOps
Languages
- English
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