Final application date

18 April, 2021

Company

Signality

About us…

Signality is an intelligent sports platform that gives sports rights holders, such as the betting and broadcasting industry and the leagues themselves, superpowers by analyzing video in real-time and extracting unprecedented datasets and statistics. When we say live, we mean milliseconds.

We use our patent-pending proprietary player tracking technology to give leagues, rights holders, and federations access to team and player performance analytics without costly installations. This enables new revenue streams for leagues, betting companies, and broadcasting/OTT.

What’s the job… 

As Computer Vision and Deep Learning Scientist, you will be responsible for designing and implementing new deep learning solutions for various sports video analysis (individual player recognition and tracking, ball tracking, event detection, etc.). You will be working with all steps of our implementation workflow in a fast paced team with cutting-edge research to push the boundaries and solve problems that haven’t been solved before. This includes problem formulation, data collection, deep networks design, training and validation, and product code delivery.

You should have…

  • MS or Ph.D. in Computer Science or equivalent engineering experience
  • 3+ years of relevant software development experience
  • Experience programming in Python
  • Experience with popular deep learning frameworks
  • Experience with machine learning algorithms
  • Computer Vision knowledge (projective geometry)
  • Excellent verbal and written communication skills

Awesome if you also have …

  • Experience with cloud computing services like AWS or Google Cloud.
  • Development contributions to open-source projects
  • Experience programming in Javascript

And has a personality that likes…

  • Attention to detail
  • Openness to constructive feedback
  • Getting the job done
  • Getting your hands dirty!
  • Eagerness to learn new skills and technologies
  • Continually improving the tools and platform that you use