SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 140,300 - 187,000 / annual
Rocket Lab Optical Systems is seeking a Senior Machine Learning Engineer II to support the U.S. Space Development Agency's Proliferated Warfighter Space Architecture (PWSA) Tranche 3 and beyond. You will develop deep learning neural networks for advanced Electro-Optical (EO/IR) image processing, solving mission-critical space domain and Intelligence, Surveillance, and Reconnaissance challenges for Department of Defense and Intelligence Community customers.
In this role, you will develop computer vision algorithms and deep neural networks for image and video processing chains, collaborating with researchers and engineers on artificial intelligence, machine learning, and computer vision initiatives. You will work with physics-based image simulation frameworks to scale training and validation data, design and train machine learning models for Optical Systems applications, and perform rapid prototyping and enhanced development for integration into operational systems. Additional responsibilities include troubleshooting, bug fixes, and maintenance of existing and new systems, as well as staying current with ML research to evaluate new tools, frameworks, and techniques.
Rocket Lab's Space Systems division has enabled more than 1,700 missions, ranging from interplanetary exploration and in-space manufacturing to national security and defense initiatives. The division has built spacecraft, payloads, and components for missions to the Moon and Mars, working with partners including NASA, the Space Development Agency, and the U.S. Space Force.
REQUIREMENTS:
- Bachelor's degree and 8+ years of experience, or Master's degree or 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 building deep learning neural networks (e.g., CNN) for computer vision, image processing, or analyses (object detection, image segmentation, 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 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
