Responsibilities

• Research on machine learning models for a wide range of AI applications including computer vision, computer graphics, natural language processing, audio and speech synthesis;
• Prototype and iterate on state-of-the-art research against proprietary, in-house software;
• Run and analyze machine learning experiments to diagnose problems and understand which changes are real improvements;
• Collaborate closely with a small team to balance the need for flexibility and iteration speed in research with the need for stability and reliability in a complex project;
• Understand our high-level research roadmap to help plan and prioritize future experiments;
• Build large-scale end-to-end machine learing systems from researching a prototype to production deployment.
  
  
  

Requirements

• M.S./ PhD in Computer Science, Mathematics, Physics, Engineering, Statistics or other related technical major fields; or equivalent industry experience;
• Excellent software development skills in Python;
• Strong programming skills and the ability to write performant, reusableand clean code;
• Proficiency in at least one major deep learning framework such as PyTorch, TensorFlow, MXNet, etc;
• Solid knowledge of best practices, techniques, and tricks in training deep learning models;
• Familiar with current state of academic and industry research;
• Experience with building machine learning platforms and infrastructure in production and at scale;
• Experience with deploying deep learning models in the cloud;
• Effective communication skills and ability to work in an agile environment;
• Strong sense of project ownership and personal responsibility;
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading conferences.
  
  
  

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