Machine Learning Engineer

Overview Position Title: Machine Learning Engineer Position Type: Full-time, On-Site Location: Huntsville, AL Clearance: Active TS Description Waypoint’s client is seeking a Machine Learning Engineer to support mission-critical efforts within a secure environment at the Missile and Space Intelligence Center. This role focuses on developing, integrating, and operationalizing machine learning solutions that support advanced analytics and intelligence capabilities. The selected candidate will work across the full machine learning lifecycle, from building data pipelines and training models to deploying and monitoring production systems. This position requires a strong blend of software engineering and data science expertise, with a focus on scalability, performance, and system integration. Responsibilities Integrate machine learning systems into existing software architectures and enterprise platforms Design, build, and optimize data pipelines to support model training and inference Develop, test, and deploy machine learning models into production environments Manage transition from prototype to production, including deployment pipelines and monitoring solutions Monitor model performance, including handling model drift, rollback, and failure scenarios Conduct experiments and testing to evaluate and improve model accuracy and performance Write clean, maintainable, and testable code in Python and related technologies Collaborate with cross-functional teams to integrate ML capabilities into mission systems Utilize CI/CD pipelines and GitOps practices to support automated deployment and version control Support development in Linux and Windows environments Required Active TS clearance (with ability to obtain TS/SCI with CI Polygraph) Bachelor’s degree in Computer Science, Mathematics, Statistics, Physics, or related technical field Minimum 12+ years of overall experience, including 1–3 years working with machine learning frameworks Strong programming skills in Python Experience with machine learning frameworks, libraries, and data modeling techniques Solid understanding of the machine learning lifecycle Experience working with SQL and NoSQL databases Experience working in Linux and Windows environments Familiarity with CI/CD pipelines and Agile development methodologies Understanding of software design and system integration principles Desired Active TS/SCI with CI Polygraph (desired) Experience working with large-scale (petabyte-level) datasets Experience supporting multi-INT analytics environments Experience deploying, monitoring, and scaling machine learning models in production Experience with tools such as Docker, Jupyter Notebooks, PostgreSQL, GitLab, and GitHub Experience implementing GitOps workflows Experience working in secure or classified environment #J-18808-Ljbffr