Computer Vision Researcher

Permanent

  • Job ID: 300
  • Job Type(s): Permanent
  • Categories: Data Analytics, Data Scientist
  • Posted February 4, 2021
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Enso is recruiting for a Computer Vision Researcher, partnering a fun, dynamic, fast growing team in Belfast. Our brand-new client brings the latest in video analytics powered by deep learning Artificial Intelligence to one of the oldest most essential industries in the world. They provide the next generation of ruminant livestock monitoring solutions to improve the way their clients work.

 

Following a recent investment, our client is now building a world class team of software in their Belfast offices to deliver on their mission.

 

The Role:

As a Computer Vision Researcher within the team you will be empowered to create first-in-class algorithms using the latest video analytics technologies powered by deep learning AI to provide new insights autonomously, in a way that is not available to today.

 

  • Selecting the best methodology to solve real world problems.
  • Implementing methodologies to provide insights within the cloud platform.
  • Staying up-to-date with the latest publications.
  • Producing statistical metrics to report on the performance of the algorithms.
  • Working as part of a small, multi-modality team to deliver robust algorithms with a focus on rapidly delivering value to the customer.
  • Learning the domain alongside customers and resident domain experts.
  • Building pipelines to ensure early feedback from algorithm improvements.
  • Defining processes to ensure repeatability of the algorithm building process.
  • See algorithms through from design to delivery to the customer.

Required Experience:

  • A PhD with a machine learning, mathematical or equivalent background.
  • Experience developing deep learning algorithms.
  • A self-motivated and eager to win mindset.
  • Computer vision
  • Image analysis
  • Object detection & tracking
  • Key point detection
  • Image classification
  • Delivering algorithms into a production environment.
  • The use of Amazon Web Service.
  • Video analytics.
  • Applying knowledge in a commercial setting.
  • Building models for edge devices.

 

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