Sr. AI/ML Engineer I (6813)

MetroStar•Reston, VA

About The Position

As a Sr. AI/ML Engineer I, you will design, build, deploy, and maintain production-ready AI and machine learning solutions, leveraging advanced ML techniques to support Retrieval-Augmented Generation (RAG) capabilities and drive mission-focused outcomes. In this role, you will serve as a trusted technical advisor, ensuring secure and effective system integration, while translating complex findings into actionable insights for diverse audiences across the organization. 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

6 years experience; minimum.
Bachelor's degree or equivalent experience
Active TS/SCI CI Poly Clearance
Extensive experience using open-source models to the largest extent possible or provide a comparable analysis and justification for using proprietary models.
Expert experience with at least two of following AI/ML methods: Generative AI/LLMs, NLP, RAG, and neural networks.
6 years experience with at least two following technologies: Python, R, Anaconda, Numpy, TensorFlow, Keras, SciKit-Learn, and Postgres
6 years experience designing, implementing, and maintaining data architecture and services to be used for AI/ML.
Able to maintain the AI/ML models through user stories and DevSecOps CI/CD pipeline including any optimization and evaluation of alternatives.
Expert experience designing, developing, and deploying AI/ML solutions into classified AWS cloud environments at IL6+.
Strong experience with designing, developing, and deploying containerized AI/ML solutions.

Responsibilities

Build, train, operationalize and maintain AI/ML models in production.
Apply machine learning techniques to support retrieval augmented generation.
Present results to a diverse audience in presentation or report form.
Support architectural leadership, technical support, and advisement services to ensure system technologies are integrated and meeting the appropriate security requirements.
Perform data analytics on program related or system related activities, including assessing performance and manual processes implementing methods/algorithms to automate and optimize.