Senior Machine Learning Engineer II (EO/IR Image Analysis)

Description

The company builds rockets, spacecraft and critical subsystems. Its Space Systems division makes complete spacecraft, payloads and components such as solar panels, flight software, star trackers, optical systems, separation systems and radios.

Space Systems has supported more than 1,700 missions, from interplanetary exploration and in-space manufacturing to national security and defense work. It has built hardware for Moon and Mars missions and works with NASA, the Space Development Agency and the U.S. Space Force.

The Optical Systems team develops sensing solutions for space domain and Intelligence, Surveillance, and Reconnaissance (ISR) work for Department of Defense and Intelligence Community customers. It builds on more than 20 years of electro-optical and infrared (EO/IR) systems work, with designs for space, ground and airborne settings.

The role is in Tucson, AZ. You will help deliver Tranche 3 of the Space Development Agency's Proliferated Warfighter Space Architecture (PWSA) and later work by building deep learning neural networks for EO/IR image processing. The team works to tight deadlines.

Responsibilities

• Build computer vision algorithms and deep neural networks for image and video processing pipelines.
• Partner with researchers and engineers on AI, machine learning and computer vision work.
• Use physics-based image simulation frameworks to scale up training and validation data.
• Design, train and deploy machine learning models for optical systems.
• Prototype quickly and extend development so that work can move into operational systems.
• Troubleshoot, fix bugs in, and maintain existing and new systems.
• Keep up with ML research and assess new tools, frameworks and methods.

Requirements

• Bachelor's degree and 8+ years of experience, or a master's degree or Ph.D. in Computer Science, Electrical and Computer Engineering, Mechanical Engineering, Physics or a related field.
• Solid grounding in math and ML fundamentals, including model selection, architecture, training, validation, testing and deployment.
• Experience building deep learning CNNs for computer vision, image processing or analysis, such as object detection, image segmentation and tracking.
• Strong math skills, especially linear algebra and optimization theory.
• Proficiency in Python.
• Experience with deep learning libraries such as Keras, TensorFlow and PyTorch.
• Software engineering fundamentals: version control, testing, CI/CD and containerization.
• Proficiency in C/C++/Rust.
• Experience curating high-quality, real-world datasets for training deep learning models.
• U.S. citizenship is required because of program requirements.
• Ability to obtain and maintain a U.S. Government security clearance.
• TS/SCI security clearance.

Conditions

Based in Tucson, AZ.

The role may require long periods of sitting, standing, walking and computer work, with occasional exposure to moderate noise, dust and fumes in production areas.

For U.S. offices: to meet U.S. export rules for space technology, including ITAR, you must be a U.S. citizen, a lawful permanent resident, a refugee or asylee lawfully admitted to the U.S., or eligible to obtain the required authorizations from the U.S. Department of State and/or Department of Commerce, as applicable.

For New Zealand offices: background checks, including nationality checks, are completed before any offer. You must be eligible to access ITAR-regulated equipment and data. You may be ineligible if you do not hold citizenship of Australia, Japan, New Zealand, Switzerland, the European Union or a NATO member country, or if you hold ineligible dual citizenship or nationality.