Scopio Labs

Senior Research Engineer, Computer Vision

Scopio Labs

full-time

Posted on:

Origin:  • 🇮🇱 Israel

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Job Level

Senior

Tech Stack

DockerLinuxPythonPyTorchTensorflow

About the role

  • Contributing expertise to the team to extract maximum value from available visual data
  • Serving as a knowledgeable resource, capable of respectfully teaching and guiding others, while continuously learning and growing
  • Researching and implementing AI technology, including deep learning and classical computer vision approaches
  • Designing and developing efficient, clear and production-ready Python code to ensure rapid and seamless product integration
  • Actively participating in researching new directions: sharing ideas and best practices, defining data requirements, contributing to improving the team's internal research tools, and supporting other team members with their research efforts
  • Working within a team transforming hematology into a big-data science to enable better healthcare outcomes

Requirements

  • B.Sc. in math, physics, electrical engineering, computer science, or a related field is required
  • M.Sc. particularly with a background in computer vision is strongly preferred
  • 5+ years of industry experience in a similar role
  • Strong mathematical background with an understanding of deep learning networks
  • Proficiency with PyTorch and/or TensorFlow
  • Excellent software design and Python programming skills
  • Familiarity with modern software development processes and tools, with an emphasis on code quality and documentation
  • Ability to lead concept development from design through implementation, testing, and deployment
  • Aptitude for analyzing computer vision challenges and collaborating with experts to deliver state-of-the-art classic, ML, and/or DL solutions
  • Experience optimizing code using CPU & GPU (ideal)
  • Experience with multiprocessing, Docker, and Linux memory management (ideal)
  • Experience with MLOps, both training and serving (ideal)
  • Background in medical devices (ideal)