Space Sensing AI/ML Research

BlueHalo, an AV company, is seeking a highly motivated and skilled Space Sensing AI/ML Research Scientist to join our team in the development, testing, and deployment of machine learning and innovative computational methods for cloud-based and on-orbit/edge computing systems. These systems are critical to supporting a proliferated space-based sensor network architecture aligned with USSF goals of assured, resilient, and timely information delivery to the warfighter.

The ideal candidate will work on dynamic, multi-phenomenology, and multi-modality data collection processes, including electro-optical/infrared (EO/IR), radar, and radio frequency (RF) sensors. This role includes working closely with advanced sensor development teams and collaborating with partners across the R&D lifecycle-from design and prototyping through launch and flight.

Primary Responsibilities:

Design & Develop AI/ML Methods: Lead the creation of cutting-edge AI and machine learning techniques for processing and analyzing multi-modal sensor data from space-based systems, including EO/IR, radar, and RF.

Automated/Autonomous Data Processing: Develop and demonstrate automated and autonomous data processing workflows to evaluate the performance of existing sensor designs and inform the development of next-generation sensing concepts.

Object Detection & Classification: Design algorithms for the autonomous detection, tracking, and classification of objects in space, particularly in complex or degraded environments.

Sensor Data Quality Assessment: Analyze, validate, and assess the quality and latency of mission-critical information derived from diverse sensor data sets to support real-time decision-making.

Imagery & Scene Simulation Analysis (Optional, if applicable): Analyze space-based imagery and simulated background scenes to optimize AI/ML methods for object classification and identification.

Collaboration with Sensor Teams: Work in close coordination with EO/IR sensor development teams to prototype and refine advanced space-based surveillance technologies.

Cross-Organizational Collaboration: Engage with government agencies, industry partners, and academic collaborators across the space community. Contribute to efforts spanning R&D, system design, build, test, and deployment. Required Qualifications:

A professional science or engineering (S&E) degree from an accredited academic institution (e.g., Computer Science, Electrical Engineering, Aerospace Engineering, Physics, or related field)

Demonstrated experience applying AI, machine learning (ML), and deep learning (DL) for autonomous decision-making in complex systems

Knowledge of EO/IR spectroscopy, radar, RF sensing, and multi-sensor fusion techniques for space-based systems

Familiarity with cloud computing technologies, edge computing platforms, and AI/ML hardware/software in distributed environments

Must be able to obtain and maintain a Secret security clearance Preferred Qualifications:

Experience with space-based sensor systems for surveillance, reconnaissance, and situational awareness

Background in space sensor fusion, object tracking, and anomaly detection

Familiarity with AI/ML tools and frameworks such as TensorFlow, PyTorch, and scikit-learn

Experience working on cross-functional teams and collaborating with government, industry, and academia

Equal Opportunity Employer

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