Sr. AI/ML Engineer I (6438)

MetroStar•Washington, DC

17h•Remote

About The Position

As Sr. AI/ML Engineer I , you’ll MetroStar is seeking an AI / ML Engineer to support a high-visibility, enterprise AI-enabled financial compliance initiative for the Department of War. This mission-critical program modernizes financial system compliance and audit workflows across more than 180 systems. You will design, develop, and deploy AI models that power automated compliance translation, anomaly detection, semantic search, and executive-level decision support. This is a remote role with preference for candidates local to the DMV area who can attend in-person meetings as required. We know that you can’t have great technology services without amazing people. At MetroStar, we are obsessed with our people and have led a two-decade legacy of building the best and brightest teams. Because we know our future relies on our deep understanding and relentless focus on our people, we live by our mission: A passion for our people. Value for our customers. If you think you can see yourself delivering our mission and pursuing our goals with us, then check out the job description below!

Requirements

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 designing and deploying machine learning models in regulated environments
Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or similar
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

Nice To Haves

Experience supporting DoD or regulated federal environments preferred

Responsibilities

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