Senior ML Engineer - Real-Time Fraud & Identity

LexisNexis Risk Solutions; England; On-site; GBP 70,000 - 120,000; Full time

Job summary

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

The role emphasizes owning DevOps, security, and end-to-end delivery, collaborating with data scientists, architects, and QA to implement automated training, monitoring, and evaluation workflows.

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

Software engineering

DevOps

Secure engineering

Independent execution

Tools

Snowflake

dbt

Snowpark

Snowflake ML

Job description

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

The role emphasizes owning DevOps, security, and end-to-end delivery, collaborating with data scientists, architects, and QA to implement automated training, monitoring, and evaluation workflows.