Principal Machine Learning Engineer (EO/IR Image Analysis)

Rocket Lab’s Space Systems division builds complete spacecraft, precision payloads to the components and subsystems that allow them to thrive in space including solar panels, flight software, star trackers, optical systems, separation systems, and radios.

The Space Systems division has enabled more than 1,700 missions, ranging from interplanetary exploration, in-space manufacturing to national security and defense initiatives. We have built spacecraft, payloads, and components for missions to the Moon and Mars, working with partners including NASA, the Space Developm...

Rocket Lab Optical Systems solves mission-critical space domain and Intelligence, Surveillance, and Reconnaissance challenges for Department of Defense and Intelligence Community customers. Our vision is to revolutionize the space-based payload market with innovative and novel designs for space, terrestrial, and air...

Contribute your experience to developing solutions for real-world problems.
Design, train, and deploy machine learning models for Optical Systems applications
Build and maintain ML pipelines for data ingestion, feature engineering, training, and inference.
Collaborate with other researchers/engineers on artificial intelligence, machine learning, and computer vision.
Preform rapid prototyping and enhanced development to be integrated into operational systems.
Perform troubleshooting, bug fixes, and maintenance of existing and new systems.
Stay current with ML research and evaluate new tools, frameworks, and techniques

Bachelor's degree and 12+ years of experience, master’s degree or a Ph.D. in Computer Science, Electrical and Computer Engineering, Mechanical Engineering, Physics, or related field
Strong background in machine learning including model selection, architecting, training, validation, testing, and deployment
Experience in building deep learning neural network for computer vision, image processing, or video analysis (e.g., object detection, image segmentation, and tracking)
Strong math background, particularly linear algebra
Proficiency in Python
Experience with deep learning libraries (Keras, TensorFlow, Pytorch, etc)
Software engineering fundamentals: version control, testing, CI/CD, containerization
S. citizenship is required, due to program requirements
Ability to obtain and maintain an U.S. Government Security Clearance
Proficiency in C/C++/Rust
Experience curating quality, real-world datasets for training deep learning models
TS/SCI security clearance

Citizenship of AU / NZ / EU / NATO