AI/ML – Voice Interaction R&D Engineer, Siri Understanding


Job Overview

Key Qualifications

  • 3+ years of proven experience with scalable machine learning technologies for speech/voice applications.
  • Depth and breadth of ML expertise, strong solid understanding of ML algorithms (deep learning, classification, clustering, etc.) and applied statistics.
  • Hands-on experience working with machine learning libraries, TensorFlow and PyTorch.
  • Strong programming skills in C/C++ is preferred.
  • Ability to analyze systems, design and implement experiments, improve ML algorithms and models, with a comprehensive thinking bringing algorithms, data, and models together.
  • Familiarity with large-scale data analysis using distributed systems is a plus.
  • Practical experience in using non-audio sensors/signals
  • Outstanding written and verbal communication skills, ability to work optimally in multi-functional teams.
  • Description

    You will be a part of a team that is responsible for a variety of user-interaction related research and development activities including wake-up word detection, speaker recognition, end-of-turn detection, conversational turn-taking, sensor fusion, and related tools and infrastructure. Our team leverages supervised and unsupervised learning to build scalable technologies that work seamlessly and flawlessly across Apple devices. As part of Siri Understanding, we work very closely with other teams within and outside Siri to help our users interact with Siri in convenient and intuitive ways.You should be passionate about building extraordinary products that are used by millions of people. Attitude and willingness to work hands-on in data collection, experimentation, applying state-of-the-art algorithms, and building and testing tools, is a must. You will be working closely with engineers and scientists from a number of other teams at Apple, and are encouraged to thrive in a highly collaborative environment with rapidly changing priorities. You are excited about applying your technical skills and background in novel and imaginative ways, and be willing to target moonshots!

    Education & Experience

    Ph. D. in a Machine Learning or related field, or M.S. with 3+ experience in Machine Learning

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