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About the Role
As a Software Engineer, you will build and deploy machine learning-powered services, tools, and full-stack applications that support fraud and identity analytics. You’ll work across backend systems, model-serving infrastructure, and user-facing applications, collaborating with cross-functional teams to deliver scalable, secure, and reliable solutions in production environments.
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.
Requirements
- 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.
- LLMs, embeddings, or vector databases.
- Behavioural, graph, or anomaly detection models.
- dbt, Snowpark, or Snowflake ML.
Experience Level
- 4+ years software engineering
Benefits
- Country specific benefits
About the Company
- LexisNexis Risk Solutions is the essential partner in the assessment of risk.
- Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience.
- Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management.
- You can learn more about LexisNexis Risk at https://risk.lexisnexis.com/
Equal Opportunity
- 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.
- USA Job Seekers: EEO Know Your Rights.