W1siziisijiwmtgvmtevmdivmtevmjevmzkvmtu2l3nodxr0zxjzdg9ja181mtk4otm4njkuanbnil0swyjwiiwidgh1bwiilciymdawedewmdbcdtawm2uixv0

VP of Computer Vision (AI Start-Up)

VP of Computer Vision (AI Start-Up)

  • Location

    London, England

  • Sector:

    Machine Learning & AI

  • Job type:

    Permanent

  • Salary:

    £130000 - £140000 per annum + equity, benefits

  • Contact:

    Anna Heneghan

  • Email:

    aheneghan@understandingrecruitment.co.uk

  • Job ref:

    BBBH11232_1646629215

  • Published:

    3 months ago

  • Expiry date:

    2022-03-14

  • Consultant:

    #

VP of Computer Vision (AI Start-Up)

How can you use Machine Learning to prevent abuse online?

Are you looking for a more autonomous and decision making role?

We are looking for a VP of Computer Vision (AI Start-Up) to join a London based organisation that are looking to solve cyberbullying, online abuse and more. This VP will be using Vision and Natural Language Processing to find real-world solutions to content moderation.

This VP of Vision will be collaborating with their Speech team, alongside the surrounding leadership team. You will be using your prior AI experience to build out this experimental tech solution.

As a VP, you will need to have experience with Computer Vision and/or Speech / Audio Processing. You will be a team player, able to work in a daring environment and be able to both mentors and manage junior employees.

You will be entitled to; VP of Computer Vision (AI Start-Up):

  • Competitive compensation
  • Equity offering
  • The ability to take ownership of your work
  • Make key technical decisions
  • Progress quickly in your career

Key Words: VP of Computer Vision (AI Start-Up); AI, Artificial Intelligence, Machine Learning, ML, NLP, Deep Learning, GANs, Deep Neural Networks, CNNs, Computer Vision, Image, Video, Processing, 3D, Object Detection, Scientist, Researcher, PhD, Post Doctoral, Research Fellow, Lecturer, Reinforcement Learning, ACML, NIPS, ICML, ICVPR, Publications, Conferences, Journals, Bayesian Inference, Generative Models, Audio Processing, Speech