Design and implement machine learning models supporting financial compliance validation and data standardization
Develop AI-assisted translation engines that map legacy financial artifacts to enterprise standards
Build semantic retrieval and embedding pipelines to support explainable compliance workflows
Integrate large language models into secure, production-grade environments
Develop model evaluation frameworks and continuously improve performance, trust, and explainability
Partner with Data Engineers, DevSecOps, Full Stack Engineers, and Financial SMEs to deliver scalable AI-enabled capabilities

Active Secret clearance required
Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related field
Minimum 5 years of AI/ML engineering experience
Experience supporting DoD or regulated federal environments preferred
Experience designing and deploying machine learning models in regulated environments
Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or similar
Experience building and optimizing Retrieval-Augmented Generation (RAG) workflows
Familiarity with embedding models, vector databases, and semantic search architectures
Experience with prompt engineering, structured output parsing, and model evaluation frameworks
Understanding of model governance, bias mitigation, and explainability in compliance-driven contexts
Experience integrating AI models into secure, containerized production environments

Senior AI/ML Engineer

Key skills