Principal Machine Learning Engineer (EO/IR Image Analysis)

Location: Tucson, Arizona, United States; onsite work in a U.S. office

Company

hirify.global is an end-to-end space company developing rockets, spacecraft, optical systems, and critical subsystems for commercial, civil, and national security missions.

What you will do

• Design, train, validate, test, and deploy machine learning models for optical systems applications.
• Build and maintain ML pipelines for data ingestion, feature engineering, training, and inference.
• Develop deep learning neural networks for electro-optical and infrared image processing, including computer vision applications.
• Collaborate with researchers and engineers on artificial intelligence, machine learning, and computer vision solutions.
• Prototype rapidly and integrate enhanced software into operational systems.
• Troubleshoot, fix bugs, maintain systems, and evaluate new ML tools, frameworks, and research techniques.

Requirements

• Bachelor’s degree with 12+ years of experience, or a master’s degree or Ph.D. in computer science, engineering, physics, or a related field.
• Strong machine learning background covering model selection, architecture, training, validation, testing, and deployment.
• Experience building deep learning neural networks for computer vision, image processing, or video analysis, including object detection, segmentation, or tracking.
• Strong mathematics background, particularly linear algebra, and proficiency in Python.
• Experience with Keras, TensorFlow, PyTorch, or similar deep learning libraries, plus version control, testing, CI/CD, and containerization.
• U.S. citizenship is required, and the ability to obtain and maintain a U.S. Government Security Clearance is required.

Nice to have

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

Culture & Benefits

• Work on space, defense, and intelligence missions involving optical and infrared sensing systems.
• Collaborative environment spanning machine learning, artificial intelligence, computer vision, and optical systems engineering.
• Role may involve prolonged sitting, standing, walking, computer work, and occasional exposure to moderate noise, dust, and fumes in production areas.
• Work takes place under tight deadlines with an emphasis on rapid innovation, teamwork, and delivery of operational systems.