Machine Learning Engineer

Astrion; Huntsville (AL); On-site; USD 110,000 - 150,000; Full time

Job summary

Astrion seeks a Machine Learning Engineer to join our analytics team on an MLOps workload for a government customer in Huntsville, AL. You will develop and deploy AI/ML models, build data pipelines, and ensure production readiness.

The role requires TS/SCI with CI Poly, 1–3 years of ML experience, Python proficiency, and strong knowledge of databases. You’ll work with Docker, GitLab/GitHub CI/CD, and open-source tools in a Linux/Windows environment.

Qualifications

• 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.

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.

Skills

Python

ML frameworks

CI/CD practices

SQL/NoSQL databases

Operating Systems (Linux/Windows)

Education

Bachelor's degree in Computer Science/Statistics/Math/Physics

Tools

Docker

PostgreSQL

Jupyter Notebooks

Job description

Overview

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