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