Principal Machine Learning Engineer

SAIC

1d • Remote

About The Position

SAIC is seeking a highly motivated Principal Machine Learning Engineer to join our team of professionals providing technical and program support for the V-22 aircraft.

 The  Principal Machine Learning Engineer understands complex problems, develops solutions, and makes predictions based on collection and analysis which are then interpreted and communicated to assist with making informed organizational decisions. This individual will use statistical techniques and machine learning algorithms to identify patterns within large amounts of structured and unstructured data, build predictive models, and develop data-driven solutions. The ideal candidate will utilize their data expertise and apply leadership and analytical skills to the mission, contributing to its success.

Requirements

• Bachelors in in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related STEM field and nine (9) years or more of experience in of AI/ML experience in defense or intelligence environments; Master's degree and seven (7) years or more of experience.
• U.S. Citizenship required.
• No dual citizenship.
• Must have an Active Secret clearance to start
• Six (6) or more years of experience and a strong background in Machine Learning and Computer Vision, including classical techniques and deep learning-based approaches.
• Practical experience working with defense programs and an understanding of program requirements and milestones
• Hands-on experience with computer vision libraries such as OpenCV, PyTorch, TensorFlow, etc.
• Comfortable operating in Linux environments for development and deployment tasks.

Nice To Haves

• Proficiency in containerization and orchestration tools (e.g., Docker, Kubernetes) for scalable deployment.
• Understanding ML Ops practices including CI/CD pipelines, model versioning, and automated retraining.
• Experience with real-time systems and latency-sensitive applications
• Prior work with defense, maritime, or aerospace systems

Responsibilities

• Design and implement models and algorithms to support program objectives in detecting maintenance and readiness trends and issues.
• Analyze and integrate data from various sensor modalities and enterprise data sources in logistics, maintenance, and supply
• Develop scalable data pipelines and orchestrate workflows using
• Write efficient code, typically in Python, and shell scripts for deployment and automation tasks.
• Work in a Linux development environment, emphasizing scripting, debugging, and system-level operations.
• Collaborate with cross-functional teams including ML engineers, software developers, and systems integrators.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Number of Employees: 5,001-10,000 employees