Join a premier defense organization in Huntsville as a Machine Learning Engineer, where you will bridge the gap between advanced research and mission-critical production. This onsite role offers the opportunity to deploy sophisticated intelligence and analytics solutions that support national security initiatives. We are seeking a cleared professional with over a decade of experience to lead the integration of scalable ML models into complex software architectures.
About the role
As a Machine Learning Engineer within our Aerospace and Defense division, you will play a pivotal role in transforming theoretical intelligence concepts into robust, production-ready systems. This position is situated at the intersection of data science and software engineering, requiring a professional who understands how to build, deploy, and maintain models within highly secure environments. You will work alongside a dedicated team of technical experts in Huntsville, Alabama, focusing on the delivery of advanced analytics that provide actionable insights for critical government missions.
Your primary focus will involve the end-to-end lifecycle of machine learning solutions. This includes the design and integration of ML systems with broader software platforms, ensuring that every model is optimized for performance and scalability. You will be responsible for building the underlying data pipelines that fuel these workflows, transitioning prototypes into stable production environments. Because our work supports high-stakes intelligence operations, you will also be tasked with rigorous monitoring of model performance, addressing issues such as model drift and failure scenarios through proactive rollback and maintenance strategies.
The technical environment is diverse and demanding, requiring proficiency across both Linux and Windows platforms. You will utilize a modern stack including Python, Docker, and Jupyter Notebooks, while managing data across PostgreSQL and various SQL/NoSQL databases. Collaboration is at the heart of our success; you will work closely with cross-functional teams to ensure that all machine learning initiatives align with the overarching system architecture. By implementing GitOps practices and supporting CI/CD workflows, you will help maintain a high standard of code quality and deployment efficiency.
Beyond the technical execution, this role demands a commitment to documentation and experimentation. You will conduct thorough testing to validate model performance and write clean, maintainable code that can stand the test of time. As a senior member of the technical staff, your 12+ years of professional experience will be vital in navigating the complexities of large-scale data processing. This is an opportunity to apply your expertise to petabyte-scale challenges while maintaining the highest levels of security and integrity required by our government partners.
Responsibilities
- Design and integrate machine learning systems with enterprise-level software platforms and infrastructure
- Build and optimize scalable data pipelines to support complex machine learning workflows
- Transition machine learning prototypes into production-ready solutions for intelligence applications
- Develop and manage automated deployment pipelines for machine learning models
- Monitor model performance in real-time to address model drift, failures, and necessary rollbacks
- Conduct rigorous testing and experimentation to document and improve model performance metrics
- Write clean, scalable, and maintainable code primarily using Python and associated libraries
- Collaborate with technical architects to ensure ML solutions align with broader system requirements
- Support CI/CD workflows and GitOps practices to streamline development and deployment cycles
- Manage and query large datasets within PostgreSQL and other SQL/NoSQL database environments
Requirements
- Active TS/SCI security clearance with the ability to obtain a CI Polygraph after onboarding
- United States Citizenship is required for this position
- Bachelor degree in Computer Science, Statistics, Mathematics, Physics, or a related quantitative discipline
- Minimum of 12 years of overall professional experience in technical or engineering roles
- One to three years of hands-on experience specifically working with machine learning frameworks
- Strong professional programming experience in Python for data science or engineering
- Deep understanding of machine learning libraries, data structures, and data modeling principles
- Proven experience working with SQL and NoSQL databases and managing data integrity
- Knowledge of CI/CD pipelines, Agile development methodologies, and software design principles
Preferred Qualifications
- Master degree in a related field with 12 years of professional experience
- Bachelor degree in a related field with 17 years of professional experience
- Experience working with petabyte-scale datasets and multi-source intelligence analytics
- Proven track record of deploying, monitoring, and scaling ML models in production environments
- Advanced proficiency with Docker, GitLab, and containerization strategies in secure environments
- Experience with Linux and Windows system integration for machine learning applications
Compensation
$110,000 – $138,000
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