Computer Vision Research Engineer

4-7 years
1 Applied
Job Description


Job description
Job Responsibilities:

  • Help build novel computer vision algorithms for multiple-object tracking
  • Create and carry out experiments
  • Offer remedies for the flaws in the current algorithms
  • Aid the team in expanding into a broader range of AI applications and markets
  • Write scientific articles and technical reports regarding the techniques you've devised

Job Requirements:
  • Master's degree or Ph.D. in Computer Vision, Engineering, Computer Science (or equivalent experience)
  • At least 4+ years of relevant experience in modern computer vision research and development
  • 4+ years of Python experience
  • 3+ years experience in PyTorch and/or Tensorflow
  • Familiarity with the state-of-the-art in object detection, multiple-object tracking, and image classification
  • Demonstrated understanding, experience working with, and ability to extend algorithms for these tasks
  • Publications in relevant venues (CVPR, ECCV, etc.) or demonstrated deployment of impactful real-world computer vision applications are a plus
  • Excellent written and verbal English communication skills
  • A track record of executing machine learning projects from start to finish and presenting results
  • Understanding of production deployment of machine learning algorithms, including MLOps and cloud-based and edge-based solutions, is a plus
  • Grant writing experience is nice to have

About
Job Source: www.turing.com

A rapidly-emerging company established to address issues with marine sustainability and conservation using the most recent findings in artificial intelligence is looking for a Computer Vision Research Engineer. The selected candidate will be responsible for writing technical papers and scientific essays about the methods developed. The company provides a technology that is tailored to meet the specific needs of each fishery. This will be a great chance for candidates to contribute to ground-breaking work in preserving some of the world's most important ecosystems and creating a more sustainable future.

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