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Rocket Lab Optical Systems, part of Rocket Lab's Space Systems division, is seeking a Scientist specializing in EO/IR (Electro-Optical/Infrared) image analysis and pattern recognition. The division delivers mission-critical space domain and Intelligence, Surveillance, and Reconnaissance solutions for Department of Defense and Intelligence Community customers, building on over 20 years of innovation in electro-optical and infrared systems.
In this role, you will develop, validate, and deploy advanced algorithms for image processing, object detection, and tracking on EO/IR space payloads. Your responsibilities will include:
• Develop, validate, and optimize algorithms for EO/IR sensor data, including noise reduction, image enhancement, image registration, correction, and pattern recognition techniques.
• Apply pattern recognition to detect, classify, and track objects in EO/IR data for mission-critical applications.
• Build and enhance modeling and simulation libraries, including developing image simulators to generate synthetic EO/IR data for algorithm development, testing, and validation.
• Support and enhance existing operational programs by maintaining and improving deployed algorithms, troubleshooting fielded systems, and ensuring ongoing performance and reliability.
• Implement and test algorithm improvements in deployed systems to support mission needs.
• Apply strong programming skills (MATLAB, Python, C/C++) to develop robust solutions for real-world mission problems.
• Analyze large and complex EO/IR datasets to extract features, identify patterns, and assess algorithm performance.
• Develop and document software tools for data collection, analysis, and performance assessment.
• Decompose high-level customer requirements into algorithm and subsystem requirements to inform software and systems engineering execution.
• Document and present algorithm performance results to technical and non-technical stakeholders, including government customers.
• Attend technical interchange meetings and represent the organization in matters pertaining to project development.
• Provide status updates on assigned tasks and program schedules.
• Support travel or off-site work as needed.
Rocket Lab's Space Systems division has enabled more than 1,700 missions, ranging from interplanetary exploration and in-space manufacturing to national security and defense initiatives, working with partners including NASA, the Space Development Agency, and the U.S. Space Force.
REQUIREMENTS:
• Bachelor's degree in physics, optical sciences, computer science, mathematics, electrical engineering, or a related technical discipline with demonstrated experience in image processing or EO/IR systems.
• Active U.S. Government Security Clearance with TS/SCI eligibility; U.S. citizenship required.
• 12+ years of professional experience.
• Demonstrated experience with MATLAB, Python, and/or C/C++ for analysis, modeling, simulation, or algorithm development.
• Strong experience designing, implementing, testing, and optimizing algorithms for EO/IR sensors, with a focus on image processing and pattern recognition.
• Strong written and verbal communication skills, with the ability to document technical work and present results to diverse audiences.
• Ability to contribute to the completion of programs and project milestones.
NICE-TO-HAVE QUALIFICATIONS:
• Master's degree or PhD in physics, optical sciences, computer science, mathematics, electrical engineering, or a related technical discipline.
• Experience with pattern recognition methods for EO/IR applications, including feature extraction, classification, and tracking.
• Experience with sensor calibration procedures (radiometric, geometric, temporal) for EO/IR systems.
• Expertise in modeling and simulation, including multiple EO/IR phenomenologies.
• Experience across all phases of product development, including proposal design architectures, requirements generation, design development, integration, verification, and transition to production.
• Experience managing or leading others in a technical and/or functional capacity within an engineering environment.
