Senior Software Engineer

ABOUT ROCKET LAB Rocket Lab is an end-to-end space company delivering responsive launch services, complete spacecraft design and manufacturing, payloads, satellite components, and more – all with the goal of opening access to space. The rockets and satellites we build and launch enable some of the most ambitious and vital space missions globally, supporting scientific exploration, Earth observation and missions to combat climate change, national security, and exciting new technology demonstrations.

Our Electron rocket has become the second most frequently launched U.S. rocket annually and has delivered more than 230 satellites to orbit, all while we work to develop Neutron, our upcoming medium‑lift, reusable launch vehicle for larger constellation deployment. Our Space Systems business designs and builds our extensive line of satellites, payloads, and their components, including spacecraft that have been selected to support NASA missions to the Moon and Mars and components used on the James Webb Space Telescope.

Rocket Lab’s Optical Systems division solves mission‑critical space domain and Intelligence, Surveillance, and Reconnaissance (ISR) challenges for Department of Defense (DoD) and Intelligence Community (IC) customers. Our vision is to revolutionize the space‑based payload market with innovative and novel designs for space, terrestrial, and airborne environments. Building on more than 20 years of electro‑optical and infrared systems innovation from Geost, Optical Systems delivers solutions to the warfighter for responsive, scalable sensing solutions across all orbital domains.

In this role, as a Senior Software Engineer I based at our Optical Systems sites in Tucson, AZ, you will support Tranche3 of the U.S. Space Development Agency’s (SDA) Proliferated Warfighter Space Architecture (PWSA) by building deep learning neural networks for advanced Electro‑Optical (EO/IR) technology.

• Collaborate with researchers on artificial intelligence, machine learning, and computer vision.
• Perform rapid prototyping and enhanced development to be integrated into operational systems.
• Contribute programming ability and experience to develop solutions for real‑world problems.
• Validate, tune, test, and deploy advanced neural networks and algorithms.
• Perform troubleshooting, bug fixes, and maintenance of existing and new code to ensure stability.
• Ability to support travel or off‑site work, as needed.

• Bachelor’s degree in physics, astronomy, mathematics, computer science, electrical engineering, mechanical engineering or equivalent discipline with 5+ years of experience.
• Experience in building deep learning neural networks for computer vision, image processing, or video analysis.
• Ability to obtain and maintain a U.S. Government Security Clearance.

• Proficiency in C++ or Python
  3.
• Experience with deep learning libraries (PyTorch and Tensor Flow).
• Experience across the deep learning life cycle, including model selection, training, validation, testing, and deployment.
• Understanding of computer vision approaches, such as object detection, image segmentation, re‑Identification, tracking, and super resolution.
• Machine learning experience with 3‑D data.
• Experience curating quality, real‑world datasets for training deep learning models.

This position may require prolonged periods of sitting, standing, walking, computer work, and occasional exposure to moderate levels of noise, dust, and fumes in production areas.

Rocket Lab provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment at Rocket Lab, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.