Senior Software Engineer Machine Learning/Fullstack
LexisNexis Risk Solutions · London Area, United Kingdom
About this role
The candidate will build and deploy ML-powered services, tools, and full-stack applications to support fraud and identity analytics. Key responsibilities include developing ML inference APIs, microservices, and data/feature pipelines, as well as building full-stack tools for model evaluation and transparency. The role involves integrating ML models into real-time production systems and implementing automated training, monitoring, and evaluation workflows. The engineer will own DevOps and security standards for assigned services and collaborate with data scientists, architects, and QA. The technical environment involves Python, Python, and Snowflake.
Skills & technologies
Nice to have
- LLMs
- embeddings
- vector databases
- Behavioural models
- graph models
- anomaly detection models
- dbt
- Snowpark
- Snowflake ML
Mentioned in this posting
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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.
- Learn more about the LexisNexis Risk team and how we work here
