At a Glance
- Tasks: Build and deploy ML-powered services and full-stack applications for fraud and identity analytics.
- Company: Join LexisNexis Risk Solutions, a leader in data-driven decision tools.
- Benefits: Generous holiday allowance, health benefits, and extensive learning resources.
- Other info: Collaborative environment with opportunities for career growth and community support.
- Why this job: Make a real impact by using advanced analytics to enhance operational efficiency.
- Qualifications: 4+ years in software engineering with strong Python and Java skills.
The predicted salary is between 60000 - 80000 £ per year.
About the Business
LexisNexis Risk Solutions provides customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. We use the power of data and advanced analytics to help our customers make better, timelier decisions. By bringing clarity to information, we ultimately help make communities safer, commerce more transparent, business decisions easier and processes more efficient.
About the role:
Build and deploy ML‑powered services, tools, and full‑stack applications supporting fraud and identity analytics. Work across backend services, model‑serving pipelines, and user interfaces.
Key Responsibilities
- Develop ML inference APIs, microservices, and data/feature pipelines.
- Build full‑stack tools to support model evaluation and transparency.
- Integrate ML models into real‑time production systems.
- Implement automated training, monitoring, and evaluation workflows.
- Use and contribute to AI‑assisted development tools.
- Own DevOps and security standards for assigned services.
- Collaborate with data scientists, architects, and QA.
Required Experience
- 4+ years software engineering (backend, full‑stack, or ML).
- Strong Python and Java.
- Snowflake or similar data‑platform experience.
- Familiarity with ML model serving and feature engineering.
- Strong ownership and independent execution.
- Working knowledge of DevOps and secure engineering.
Preferred Experience
- LLMs, embeddings, or vector databases.
- Behavioural, graph, or anomaly detection models.
- dbt, Snowpark, or Snowflake ML.
Working for you:
We offer a range of benefits to support your wellbeing and life outside work, including:
- Generous holiday allowance with the option to buy additional days
- Health screening, eye care vouchers and private medical benefits
- Wellbeing programs
- Life assurance
- Access to a competitive contributory pension scheme
- Save As You Earn share option scheme
- Travel Season ticket loan
- Electric Vehicle Scheme
- Optional Dental Insurance
- Maternity, paternity and shared parental leave
- Employee Assistance Programme
- Access to emergency care for both the elderly and children
- RECARES days, giving you time to support the charities and causes that matter to you
- Access to employee resource groups with dedicated time to volunteer
- Access to extensive learning and development resources
- Access to employee discounts scheme via Perks at Work
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
Full‑Stack Machine Learning Engineer in London employer: RELX
LexisNexis Risk Solutions is an exceptional employer that prioritises employee well-being and professional growth, offering a generous holiday allowance, comprehensive health benefits, and extensive learning resources. Our collaborative work culture fosters innovation and supports meaningful contributions to community safety and operational efficiency, making it an ideal environment for Full-Stack Machine Learning Engineers looking to make a real impact in their field.
StudySmarter Expert Advice🤫
We think this is how you could land Full‑Stack Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with current employees at LexisNexis Risk Solutions. A friendly chat can sometimes lead to job opportunities that aren't even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to ML and full-stack development. This gives you a chance to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and Java skills. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and solve problems!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining the LexisNexis Risk Solutions team. Don’t miss out!
We think you need these skills to ace Full‑Stack Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Full-Stack Machine Learning Engineer role. Highlight your experience with Python, Java, and any relevant ML projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how you can contribute to our mission at LexisNexis Risk Solutions. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects:If you've built any full-stack applications or ML-powered tools, make sure to showcase them in your application. Include links to your GitHub or portfolio so we can see your work in action. We’re all about practical experience!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details about the role and our company culture there!
How to prepare for a job interview at RELX
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, especially Python and Java. Brush up on your experience with Snowflake or similar data platforms, as this will likely come up during technical discussions.
✨Showcase Your Projects
Prepare to discuss specific projects where you've built ML inference APIs or full-stack applications. Be ready to explain your role, the challenges you faced, and how you overcame them. This will demonstrate your hands-on experience and problem-solving skills.
✨Understand the Business Context
Familiarise yourself with LexisNexis Risk Solutions and their focus on risk evaluation and operational efficiency. Being able to connect your technical skills to their business goals will show that you’re not just a coder, but someone who understands the bigger picture.
✨Prepare for Collaboration Questions
Since the role involves working with data scientists and QA teams, think of examples where you’ve successfully collaborated with others. Highlight your communication skills and how you ensure everyone is on the same page, especially when integrating ML models into production systems.
