Full‑Stack Machine Learning Engineer

LexisNexis Risk Solutions; Greater London; On-site; GBP 80,000 - 120,000; Full time

Benefits offered by this job

Generous holiday allowance

Private medical benefits

Life assurance

Contributory pension scheme

Save As You Earn share option scheme

Travel Season ticket loan

Electric Vehicle Scheme

Optional Dental Insurance

Employee Assistance Programme

Learning and development resources

Perks at Work discounts

Job summary

LexisNexis Risk Solutions is seeking an experienced engineer to build and deploy ML-powered services, tools, and full-stack applications that support fraud and identity analytics. You will work across backend services, model-serving pipelines, and user interfaces to deliver robust, scalable solutions.

You will develop ML inference APIs, data pipelines, and production-grade microservices, while integrating ML models into real-time systems and ensuring secure, auditable operations.

Qualifications

• 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.

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.

Skills

Python

Java

ML/AI

DevOps concepts

Problem solving

Tools

Snowflake

Snowpark

dbt

Vector databases

LLMs

Job description

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. You can learn more about LexisNexis Risk solutions at the link below, https://risk.lexisnexis.com/

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. You can learn more about LexisNexis Risk solutions at the link below, https://risk.lexisnexis.com/

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
• Learn more about the LexisNexis Risk team and how we work here

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.