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: Dynamic work environment with opportunities for professional growth and community support.
- Why this job: Make a real impact using cutting-edge technology to enhance community safety and business efficiency.
- Qualifications: 4+ years in software engineering with strong Python and Java skills.
The predicted salary is between 63000 - 77000 £ 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.
Summary Location: UK - London (London Wall) Type: Full time
Full‐Stack Machine Learning Engineer in London employer: RELX Group
As a leading innovator in the research community, our company offers an exceptional work environment for Java Software Engineers, fostering collaboration and creativity. With a strong emphasis on employee growth, we provide ample opportunities for professional development through hands-on projects and mentorship in a dynamic Agile setting. Located in a vibrant area, our culture promotes work-life balance and inclusivity, making it an ideal place for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Full‐Stack Machine Learning Engineer in London
✨Join Local Tech Meetups
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We think you need these skills to ace Full‐Stack Machine Learning 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 Group.
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How to prepare for a job interview at RELX Group
✨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 Group 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.
