Senior Software Engineer Machine Learning/Fullstack

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, 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