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Senior Computer Vision and Machine Learning Engineer

EINO

EINO

Software Engineering
Remote
Posted 6+ months ago

Senior Computer Vision and Machine Learning Engineer
Job Summary

eino is looking for a resourceful computer vision engineer with deep passion for building intelligent software modules for machine learning products. You will join eino’s product team to build a digital twin creator platform for connectivity solutions. Please include your previous experiences in building, shipping, and iterating on enterprise software products using cutting edge tools.

Responsibilities and Duties

  • Prototyping, building, testing, and delivering product quality computer vision modules
  • Prototyping, building, testing, and delivering product quality machine learning solutions
  • Working closely with technical leadership and product manager for fast development iterations on new features
  • Building innovate automation tools for enterprise applications

Qualifications and Skills

  • M.S. or Ph.D. in Computer Science, Electrical Engineering or related
  • 5+ years of experience in building image processing and image recognition algorithms
  • 3+ years of experience in building predictive models and optimization algorithms
  • 3+ years of industry experience developing product quality machine learning components
  • 3+ years of experience in backend Python programming
  • Deep expertise in our stack: * Python * OpenCV * Scikit-learn * Scikit-image * Tesseract * Rasterio * Neural Networks and Deep Learning * PostgreSQL

Perks

* Building innovative solutions for real-world problems
* Being part of a growing company with a strong foundation
* Educational support to grow personally, professionally, and technically
* Flexibility in working schedule

About eino:

eino is an AI-powered connectivity planning platform that holistically designs and simulates solution architecture for public and private WiFi/Cellular networks. Our SaaS platform enables network providers, systems integrators, and enterprises to automatically and efficiently plan new networks or test and expand existing ones for growth and new use-cases with digital twins.