Principal Machine Learning Engineer (EO/IR Image Analysis)

Principal Machine Learning Engineer

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 a Principal Machine Learning Engineer for Rocket Lab Optical Systems in Tucson, AZ, 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

• 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.
• Perform 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 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
• U.S. citizenship is required, due to program requirements
• Ability to obtain and maintain an 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.

What To Expect

We're on a mission to unlock the potential of space to improve life on Earth, but that's not an easy task. It takes hard work, determination, relentless innovation, teamwork, grit, and an unwavering commitment to achieving what others often deem impossible. Our people out-think, out-work, and out-pace. We pride ourselves on having each other's backs, checking our egos at the door, and rolling up our sleeves on all tasks big and small. We thrive under pressure, work to tight deadlines, and our focus is always on how we can deliver, rather than dwelling on the challenges that stand in the way.

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.