ML Software / AI Data Engineer
Leidos
ETLNumpyPandasPythonScikit-LearnSQL
Job Level
JuniorMid-Level
Tech Stack
ETLNumpyPandasPythonScikit-LearnSQL
About the role
- Automate, design, implement, and deploy monitoring, reporting, and forecasting systems for a high-performance FinTech platform
- Develop statistical models and machine learning algorithms (e.g., anomaly detection, clustering, regression) with an understanding of customer demands
- Prepare, engineer features, and analyze large-scale financial datasets
- Build and maintain production-ready ML pipelines for model training, validation, and performance monitoring
- Design and implement workflows for reporting, alerting, and forecasting
- Develop and refine LLM-powered agents to enable natural language interaction and analytics automation
- Drive the deployment and support of ML products and enable advanced workflows including natural language analytics powered by LLM agents
Requirements
- 2–4 years of experience in Data Science, including hands-on development and validation of statistical models and ML solutions
- Strong proficiency in Python and data analysis libraries (numpy, pandas, scikit-learn, LightGBM)
- Solid knowledge of database systems and ETL processes (SQL, data aggregation)
- Practical experience integrating LLM APIs and related tools (OpenAI API, MCP, Langfuse)
- Strong engineering focus on product integration and deployment
- Proficient spoken, written, and reading English skills required
- Background check, signed NDA, signed contract, and signed GDPR processor passthrough agreement required
- Bonus: Understanding of financial market data and experience working with FinTech platforms
- Bonus: Exposure to advanced LLM techniques and frameworks (e.g., RAG, LangGraph, multi-agent pipelines)
- Bonus: Experience with MLOps practices, containerization, CI/CD pipelines, and model monitoring in production
