Computer Vision Engineer

Snap Snap · Consumer · London, United Kingdom

Computer Vision Engineer for Snap's Spectacles team, focusing on developing and deploying novel ML/CV algorithms for next-generation AR glasses.

What you'd actually do

  1. Develop novel technologies for the next generation of Spectacles.
  2. Explore and advance state-of-the-art machine learning and computer vision algorithms.
  3. Develop and deploy machine learning models.
  4. Work together with our cross-functional engineering and research teams in computer vision, machine learning and graphics.

Skills

Required

  • Strong foundations in computer vision, machine learning, multi-view geometry
  • Ability to understand, debug and improve existing code as well as develop new algorithms using computer vision and machine learning techniques.
  • Strong problem-solving, debugging, and communication skills
  • Ability to run purposeful experiments and evaluate metrics objectively
  • Bachelors’ degree in a technical field such as computer science, mathematics or equivalent experience
  • Relevant industry, research, or applied experience in computer vision, machine learning, robotics, or perception
  • Experience programming in C++ or Python
  • Experience with machine learning frameworks (PyTorch, TensorFlow etc.)

Nice to have

  • Msc in related field (Computer Vision, Machine Learning)
  • 1+ years of relevant industry or research experience
  • Experience in geometric computer vision such as SLAM, VIO, tracking, multi-view 3D reconstruction, depth estimation or camera/display calibration
  • Experience with eye tracking, gaze estimation, pupil or glint detection
  • Experience with generating and using synthetic datasets for ML training
  • Experience in integrating Machine Learning models into Augmented Reality solutions

What the JD emphasized

  • state-of-the-art machine learning and computer vision algorithms
  • computer vision, machine learning, multi-view geometry
  • run purposeful experiments and evaluate metrics objectively

Other signals

  • Develop novel technologies for the next generation of Spectacles
  • Explore and advance state-of-the-art machine learning and computer vision algorithms
  • Develop and deploy machine learning models