Principal Machine Learning Engineer (EO/IR Image Analysis)

Rocket Lab Corporation•Tucson, AZ
•Onsite

About The Position

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.

Requirements

  • 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 networks 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 Haves

  • Proficiency in C/C++/Rust
  • Experience curating quality, real-world datasets for training deep learning models
  • TS/SCI security clearance

Responsibilities

  • 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
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