At a Glance
- Tasks: Design and build scalable software for fraud detection and identity verification.
- Company: Join LexisNexis Risk Solutions, a leader in risk assessment and analytics.
- Benefits: Enjoy competitive pay, flexible work options, and a focus on your well-being.
- Other info: Collaborative environment with opportunities for growth and innovation.
- Why this job: Make a real impact by turning machine learning into reliable products that help businesses thrive.
- Qualifications: Experience in software engineering with strong skills in Python and Java.
The predicted salary is between 63000 - 77000 £ per year.
Are you passionate about building scalable software that helps organisations detect fraud, verify identity, and make better decisions using advanced analytics? Do you enjoy collaborating across engineering, data science, and product teams to turn intelligent solutions into reliable products that deliver real-world customer value?
About the Business
LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management.
About the Role
You will join an engineering team building software for fraud and identity analytics. In this role, you will design, build, test, and operate scalable software products, working closely with data scientists, engineers, architects, product managers, and quality engineers. You will help bring machine learning and analytical capabilities into production systems, delivering secure, reliable, and maintainable solutions that create measurable customer value.
Responsibilities
- Design, build, test, and maintain production-grade backend services and APIs using Python and Java.
- Integrate machine learning models and analytical components into real-time and batch software workflows.
- Develop reusable application components for feature calculation, inference, decision support, and model output interpretation.
- Build internal and customer-facing tools that help users explore, evaluate, and understand analytical outcomes.
- Apply sound software engineering practices, including modular design, code review, automated testing, documentation, and continuous improvement.
- Improve system performance, reliability, security, observability, and maintainability across the software lifecycle.
- Work with data scientists to translate prototypes and research outputs into robust, well-defined product capabilities.
- Participate in delivery and operational ownership for the services you build, including deployment, incident analysis, and remediation.
Requirements
- Professional software engineering experience with a strong record of delivering production systems.
- Strong programming skills in Python and Java, including object-oriented design, clean interfaces, and maintainable application structure.
- Experience designing and developing APIs, backend services, distributed systems, or data-intensive applications.
- Solid understanding of software testing, version control, code review, CI/CD, secure development, and production support.
- Practical experience integrating machine learning models, statistical algorithms, or advanced analytics into software products.
- Ability to work with data stores and data platforms such as Snowflake, relational databases, or comparable technologies.
- Understanding of common machine learning concepts, feature engineering, inference, evaluation, and the limitations of analytical systems.
- Strong ownership, problem-solving, and communication skills, with the ability to execute independently and collaborate across disciplines.
Machine Learning Engineer/AI Engineer in London employer: RELX
RELX is an exceptional employer, offering a dynamic work environment in the heart of London where innovation meets collaboration. With a strong focus on employee wellbeing, generous benefits, and opportunities for professional growth, you will be empowered to influence strategic decisions across multiple business segments while enjoying a healthy work/life balance. Join us to be part of a forward-thinking team that values your contributions and fosters a culture of shared success.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer/AI 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 RELX 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 RELX.
✨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 RELX.
✨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 RELX 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 Machine Learning Engineer/AI Engineer in London
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 RELX.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at RELX 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 RELX
✨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 RELX 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.
