Job 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. 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. 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.

Requirements

Must-haves

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.
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.
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.

Nice-to-haves

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.

Application prep

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Keywords to mirror

aimlpython

Platform: oracle-cloud
Effort: medium