Machine Learning Engineer

Overview Machine Learning Engineer JOB LOCATION: Huntsville, Al JOB STATUS: Full-time CLEARANCE: TS/SCI w CI/Poly TRAVEL: As needed Astrion seeking a Machine Learning Engineer to join our analytics team working on an innovative MLOps workload leveraging cutting-edge technologies and supporting a government customer in Huntsville, Alabama. This role will be responsible for delivering automation to key national security missions interacting with petabyte-scale data on supercomputing resources. The ideal candidate will have a background in AI/ML model development and deployment and have experience in Python programming, handling SQL databases, and working in command line interfaces. The team will work with technologies including: Open source, commercial, and government software packages such as Docker, Python, Jupiter Notebooks, PostgreSQL, and other tools. Leverage GitOps patterns and CI/CD with tools like GitLab and GitHub. Work Environment Working conditions are normal for an office environment. Fast paced, deadline-oriented environment. May require periods of non-traditional working hours including consecutive nights or weekends (if applicable). REQUIRED QUALIFICATIONS / SKILLS TS/SCI with CI Polygraph Degree in Computer Science, Statistics, Mathematics, Physics or another quantitative field. 1-3 years of experience working with ML frameworks Programming proficiency in Python and extensive knowledge of ML frameworks, libraries data structures, and data modeling. Solid understanding of the full ML development lifecycle. Experience working with SQL and NoSQL databases. Experience with both Linux and Windows operating systems. Knowledge of CI/CD and Agile methodologies. Understanding of software design and system integration. PREFERRED QUALIFICATIONS / SKILLS Experience with petabyte scale data sets Experience with multi-INT analytics Experience deploying, monitoring, and scaling models in production environments RESPONSIBILITIES Integrate ML systems with other software components, ensuring that machine learning pipelines work within the overall product architecture. Manage the transition from prototype to production, including setting up model deployment pipelines and monitoring solutions. Construct optimized data pipelines to feed ML models; run tests and experiments and document findings. Monitor model performance post-deployment including managing model drift, rollback, and failure scenarios. Write clean, testable, maintainable code in Python and other languages. #CJ