AI/ML Engineer Principal
$120k - $160kSAIC Inc
Job ID: 2617793 Location: Chantilly, VA, US Date Posted: 2026-10-12 Category: Engineering and Sciences Subcategory: Systems Engineer Schedule: Full-Time Shift: Day Job Travel: No Minimum Clearance Required: TS.SCI_wPoly Clearance Level Must Be Able to Obtain: None Potential for Remote Work: ORA_ON_SITE
Description
SAIC is hiring a AI/ML Engineer to join a mission-driven, multi-disciplinary analysis team in Chantilly, VA. This role supports the design, acquisition, and operation of national security space systems by developing and integrating AI/ML capabilities into modeling and simulation environments for government satellite programs in Earth orbits, with a focus on mission planning and space domain awareness. Responsibilities include, but are not limited to:
Description
SAIC is hiring a AI/ML Engineer to join a mission-driven, multi-disciplinary analysis team in Chantilly, VA. This role supports the design, acquisition, and operation of national security space systems by developing and integrating AI/ML capabilities into modeling and simulation environments for government satellite programs in Earth orbits, with a focus on mission planning and space domain awareness. Responsibilities include, but are not limited to:
- Develop and apply AI/ML algorithms and workflows to support satellite mission planning, space domain awareness, and resilient mission operations.
- Perform end-to-end ML development, including data exploration, feature engineering, model training/tuning/validation, and performance assessment using supervised, unsupervised, and reinforcement learning.
- Implement and optimize algorithms for classification, tracking, anomaly detection, and decision support using optical and radar space-surveillance sensor data.
- Design, build, and maintain scalable HPC or HPC-like pipelines and workflows for large-scale model training, testing, and deployment.
- Use programming languages such as Python and/or C++ to extend modeling, simulation, and data analysis tools for space-domain problems.
- Collaborate with satellite designers, operations planners, and subject-matter experts to translate mission needs into AI/ML requirements and integrate solutions into broader modeling and simulation efforts.
- Conduct trade studies and technical assessments, review algorithms and models from internal and external teams.
- Minimum 2 years of relevant experience and Bachelor's Degree in Computer Science, Data Science, Applied Mathematics, Engineering, Physics, or related technical; a Master's degree may substitute for some years of experience.
- Experience designing, implementing, and evaluating ML algorithms (e.g., supervised, unsupervised, reinforcement learning) on real-world data sets.
- Proficiency in at least one major AI/ML programming language (such as Python or C++), including use of common ML and data libraries/frameworks.
- Experience conducting exploratory data analysis (EDA) and developing predictive models, including training, tuning, validation, and quantitative performance evaluation.
- Experience with scalable data processing or model-training pipelines in an HPC or cloud-like environment.
- Active TS/SCI with an active and current Polygraph.
- Position is fully on-site in Chantilly, VA; no remote work available.
- Experience applying AI/ML in the space domain (e.g., satellite operations, space surveillance, tracking, or space domain awareness).
- Experience with optical and/or radar sensor data for detection, classification, or tracking.
- Experience with physics-based modeling and simulation tools and integrating ML solutions into those workflows.
- Experience developing or optimizing algorithms for anomaly detection, mission planning, resource allocation, or sensor tasking.
- Experience building and operating HPC pipelines for large-scale model training and evaluation.
- Familiarity with astrodynamics, satellite mission design, or remote sensing concepts.
- Work is performed in office and classified lab environments, requiring the ability to sit or stand for extended periods and use standard office equipment.
- May involve walking between secure facilities and attending on-site meetings and demonstrations.
Vacancy posted 3 days ago
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