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Title: Machine Learning Engineer TS/SCI
Status: Full-Time (Hybrid set up after 6 months)
Location: Huntsville, Alabama
Ideal Candidate
ideal candidate is a senior Machine Learning Engineer with an active TS/SCI clearance, deep Python expertise, and proven experience deploying machine learning solutions into production environments. They are highly skilled in data pipeline engineering, CI/CD workflows, containerized deployments, and integrating ML systems within larger secure architectures. They thrive in mission-driven environments, balancing strong software engineering fundamentals with hands-on machine learning implementation and operational support.
Position Overview
A growing defense-focused organization is seeking an experienced Machine Learning Engineer to support advanced intelligence and analytics initiatives in Huntsville, Alabama. This is an onsite role supporting mission-critical projects involving large-scale data processing, machine learning model deployment, and system integration.
This role is ideal for someone who thrives in highly secure environments and has experience taking machine learning solutions from concept through production deployment.
Key Responsibilities
Title: Machine Learning Engineer TS/SCI
Status: Full-Time (Hybrid set up after 6 months)
Location: Huntsville, Alabama
Ideal Candidate
ideal candidate is a senior Machine Learning Engineer with an active TS/SCI clearance, deep Python expertise, and proven experience deploying machine learning solutions into production environments. They are highly skilled in data pipeline engineering, CI/CD workflows, containerized deployments, and integrating ML systems within larger secure architectures. They thrive in mission-driven environments, balancing strong software engineering fundamentals with hands-on machine learning implementation and operational support.
Position Overview
A growing defense-focused organization is seeking an experienced Machine Learning Engineer to support advanced intelligence and analytics initiatives in Huntsville, Alabama. This is an onsite role supporting mission-critical projects involving large-scale data processing, machine learning model deployment, and system integration.
This role is ideal for someone who thrives in highly secure environments and has experience taking machine learning solutions from concept through production deployment.
Key Responsibilities
- Design and integrate machine learning systems with broader software platforms and infrastructure
- Build and optimize data pipelines that support machine learning workflows
- Transition machine learning prototypes into production-ready solutions
- Develop deployment pipelines for machine learning models
- Monitor model performance and address model drift, failures, and rollback scenarios
- Conduct testing, experimentation, and documentation of model performance
- Write clean, scalable, and maintainable code primarily in Python
- Collaborate with technical teams to ensure machine learning solutions align with overall architecture
- Support CI/CD workflows and GitOps practices
- Python
- Docker
- Jupyter Notebooks
- PostgreSQL
- GitLab
- GitHub
- SQL/NoSQL databases
- Linux and Windows environments
- Bachelor''s degree in Computer Science, Statistics, Mathematics, Physics, or another quantitative discipline
- Minimum of 12 years of overall professional experience
- 1-3 years of hands-on experience working with machine learning frameworks
- Strong programming experience in Python
- Deep understanding of machine learning frameworks, libraries, data structures, and data modeling
- Experience with SQL and NoSQL databases
- Knowledge of CI/CD pipelines and Agile development methodologies
- Understanding of software design principles and system integration
- Active TS/SCI clearance with ability to obtain a CI Polygraph after onboarding
- Master''s degree in a related field with 12 years of experience OR
- Bachelor''s degree in a related field with 17 years of experience
- Experience working with petabyte-scale datasets
- Background in multi-source intelligence analytics
- Experience deploying, monitoring, and scaling machine learning models in production environments
- Machine Learning Model Deployment
- Python Development
- Data Pipeline Engineering
- CI/CD Implementation
- Cloud/Container Technologies
- System Integration
- Database Management