SAIC Defense & Aerospace

AI/ML Engineer Principal

Chantilly, VA In person Full-time

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, space domain awareness, and resilient operations.

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, and present clear technical briefings and recommendations to government stakeholders.
  • 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.
  • Strong verbal and written communication skills and demonstrated ability to work both independently and on small, fast-paced teams.

Clearance Requirements

Active TS/SCI with an active and current Polygraph

Position is fully on-site in Chantilly, VA; no remote work available.

Preferred Qualifications

  • 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.
  • Experience mentoring junior staff and/or leading small technical teams.
  • Knowledge of the intelligence production cycle and when to apply engineering judgment in the presence of limited or uncertain data.

Physical Requirements

  • 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.
  • Occasional travel (up to 5%) for meetings, reviews, or demonstrations.
  • 2026.10.1

Job description provided by SAIC.
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