About this opportunity
Rocket Lab lists this Principal Machine Learning Engineer opportunity in mclean, Virginia. Review the employer’s description below for duties, qualifications and application requirements.
Job description
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 airborne environments. Building on more than 20 years of electro-optical and infrared systems innovation from Geost, Rocket Lab Optical Systems delivers solutions to the warfighter for responsive, scalable sensing solutions across all orbital domains.
As Principal Machine Learning Engineer for Rocket Lab Optical Systems in Chantilly, VA, you will have the opportunity to support Tranche 3 of the U.S. Space Development Agency's (SDA) Proliferated Warfighter Space Architecture (PWSA) and beyond by building deep learning neural networks for advanced Electro-Optical (EO/IR) image processing.
WHAT YOU’LL DO
Develop computer vision algorithms and deep neural networks for image and video processing chains.
Collaborate with other researchers/engineers on artificial intelligence, machine learning, and computer vision.
Work with physics-based image simulation frameworks to scale training and validation data.
Design, train, and deploy machine learning models for Optical Systems applications.
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.
WHAT WE’RE LOOKING FOR IN A PRINCIPAL MACHINE LEARNING ENGINEER:
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 math and fundamentals of machine learning, including model selection, architecting, training, validation, testing, and deployment
Experience in building deep learning neural networks (e.g., CNN) for computer vision, image processing, or analyses, e.g., object detection, image segmentation, and tracking)
Strong math background, particularly linear algebra and optimization theory
Proficiency in Python
Experience with deep learning libraries (Keras, TensorFlow, Pytorch, etc)
Software engineering fundamentals: version control, testing, CI/CD, containerization
U.S. citizenship is required due to program requirements.
Ability to obtain and maintain a U.S. Government Security Clearance.
NICE TO HAVE:
Proficiency in C/C++/Rust.
Experience curating quality, real-world datasets for training deep learning models.
TS/SCI security clearance.
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.
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.
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.