Machine Learning Engineer with Security Clearance

Astrion

Huntsville (AL)

On-site

USD 120,000 - 160,000

Full time

27 hours ago
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Job summary

Astrion seeks a Machine Learning Engineer to join the analytics team in Huntsville, AL, delivering automation for national security missions with petabyte-scale data on supercomputing resources. You’ll focus on ML model development and deployment, Python programming, and handling SQL/NoSQL databases in a government-focused MLOps workload.

The role emphasizes transitioning prototypes to production, deploying pipelines, and monitoring ML systems, with a strong emphasis on CI/CD, GitOps, and

Qualifications

  • Degree in a quantitative field (CS/Math/Stats/Physics).
  • 1-3 years of ML experience and familiarity with ML frameworks.
  • Proficient in Python and ML libraries, data structures, and modeling.
  • Solid ML development lifecycle understanding.
  • Experience with SQL and NoSQL databases.
  • Experience on 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 within the product architecture.
  • Manage transition from prototype to production, including deployment pipelines and monitoring.
  • Construct optimized data pipelines to feed ML models and run tests/experiments.
  • Monitor model performance post-deployment, including drift, rollback, and failure handling.
  • Write clean, testable code in Python and other languages.

Skills

Python
ML frameworks
CI/CD
Agile methodologies
SQL
NoSQL
Linux
Windows OS
Software design
System integration

Education

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

Tools

Jupyter Notebooks
Docker
PostgreSQL
GitLab
GitHub

Job description

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.

Technology Stack
  • 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
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