Deep Learning Researcher/Engineer (Senior/Lead/Principal)

Company: Magic Leap, Inc.
Location: Sunnyvale, California, United States
Type: Full-time
Posted: 13.AUG.2021


Job Description We have an exciting opportunity on our Software team for a strong leader with exceptional development/research skills in the...


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. 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 3+ years of Deep Learning experience and 5+ 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 traditional computer vision topics such as 3D dDense reconstruction of environments. Deep learning techniques based passive depth estimations Semantics and scene understanding Model optimizations to run over embedded platforms and on the cloud Expert knowledge of deep learning techniques such as CNN, RNN, LSTM and GAN Familiarity with Neural architecture search and network quantization 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 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

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