Lead Computer Vision Researcher/Engineer, Hand Tracking

Sunnyvale, CA

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Posted 1 week ago

Magic Leap is an eclectic group of people who share a magical vision of the future. And we’re growing.

Our mission is to harmonize people and technology to create a better, more unified world. Our vision is to amplify the best parts of you and to advance the human spirit.

Job Description

We have an exciting opportunity on our software team for a strong leader with exceptional development/research skills in the field of Deep Learning, specifically for human and hand tracking. The primary responsibility of the Lead Deep Learning Researcher/Engineer is to drive the research and development of core perception components within the agreed upon scope and schedule as defined by the management team. The Lead will participate in release planning, scheduling, and assigning individual developers within their technical team. Qualified candidates will be driven self-starters, robust thinkers, strong collaborators, and adept at operating in a highly dynamic environment. We look for colleagues that are passionate about our product and embody our values.

Responsibilities

  • Provide leadership and mentoring to the research and development team within the Perception group
  • Lead the research and development effort of advanced product-critical deep learning components
  • Work hand-in-hand with the key stakeholders and developers across the company using deep learning
  • Support overall research engineering and architecture efforts in deep learning
  • Write maintainable, reusable code, leveraging test driven principles to develop high quality deep learning modules
  • Act as a mentor and subject matter expert with key stakeholders
  • Review individual developer's code in the team to ensure highest code quality

Qualifications

  • 2+ years of Deep Learning experience and 6+ years of Machine learning experience targeted to product development
  • Expert knowledge and leadership experience in Deep Learning in at least one of the following domains:
    • Applications of deep learning techniques to articulated objects such as:
      • Human Pose and Shape Estimation
      • Hand Pose and Shape Estimation
      • Real-time Tracking
      • Gesture/Action Recognition
    • Parametric model fitting and optimization
    • Single image 3D reconstruction
  • Expert knowledge of deep learning techniques such as CNN, Temporal-CNN, RNN, and GAN
  • Expert level experience in at least one of TensorFlow, PyTorch, or Caffe
  • Expert level in Python  (programming and debugging)
  • Knowledge of C/C++ and parallel computing paradigms such as OpenCL and CUDA is a plus
  • Knowledge of neural shape rendering and implicit shape representations is a plus
  • Knowledge of software optimization and embedded programming is a plus

Education

  • MS in Computer Science or Electrical Engineering (with minimum of 8 years of relevant experience)
  • Ph.D. is preferred (with a minimum of 6 years of relevant experience)

Additional Information

  • All your information will be kept confidential according to Equal Employment Opportunities guidelines
Job tags: 3D Reconstruction Computer Vision Deep Learning Engineering Machine Learning Python PyTorch Research RNN TensorFlow