Research Scientist, Perceptual Audio and Machine Learning

Employer

Job Description

The perception of audio is at the center of our research, as it informs our work in spatial audio, speech intelligibility, defining audio quality, and many of the AR/VR systems. As a Research Scientist on the Advanced Audio Technologies Team at Facebook Reality Labs, you will be tackling the perceptual and psychoacoustic and ML challenges that define cutting-edge augmented & virtual reality, conducting research at the intersection of basic and applied science, as it informs our technology directions and identifies opportunities for revolutions in our audio quality metrics and audio experiences.We are seeking a Research Scientist who is well versed in audio machine learning and auditory perception, and is excited about doing research that helps us inform AR/VR audio requirements and metrics towards new technologies. With a focus on hands-on audio modeling and machine learning, we are seeking an individual with additional skill and knowledge in some of the following areas: speech intelligibility, audio perceptual evaluation, design of experiments, computational modeling of the audio system, audio quality metrics, intensity, distortion, timbre, dynamics and loudness perception, etc.


Research Scientist, Perceptual Audio and Machine Learning Responsibilities:


  • Responsible for modeling different aspects of audio quality using a wide range of data science modeling approaches as well as state-of-the-art ML based techniques
  • Collaborate with colleagues to structure efficient data collection across a wide range of speech and audio applications
  • Developing ML architectures to model audio datasets (identification, classification and regression models) using both CNN and deep learning approaches
  • Work with cross-functional partners in both research and product development to understand and prioritize modeling needs
  • Employ existing knowledge of human sensory encoding and audio quality metrics to help guide modeling in the most efficient and meaningful manner
  • Communicate and share the findings from modeling cross functionality for maximum benefit across the HW organization
  • Explore opportunities to develop and expand the role of ML based modeling in new technology and product development


Minimum Qualifications:


  • Advanced Degree in machine learning, computer science, hearing science, acoustics, acoustic engineering, perceptual psychology, psychoacoustics, neuroscience, or a related field with an emphasis on perceptual modeling, audio machine learning psychoacoustics/physics, and/or metrics evaluating perceptual performance
  • 2+ years experience with MATLAB, Python, or similar program audio data analysis
  • Knowledge of the human auditory system and experience applying this model to novel situations and predict how the ear, brain, and body will respond
  • Practical experience in setting up and managing a full ML modeling pipeline (GitHub, etc.)
  • 2+ years of experience with machine learning (ML) or AI in audio (PyTorch, TensorFlow, Keras, Scikit-learn, Python, and associated audio processing toolboxes)
  • Interpersonal experience: cross-group and cross-culture collaboration


Preferred Qualifications:


  • Experience with user studies (psychoacoustics) or human factors
  • Experience in working on a team that ships product
  • Familiarity with audio system and/or VR, MR, AR platforms
  • Experience with research published in journals and international conference presentations or publications
  • Experience with statistical analysis tools (e.g. SPSS, SAS, R, XLstat, and/or JMP)
  • MSc or PhD in machine learning, computer science, hearing science, acoustics, acoustic engineering, perceptual psychology, psychoacoustics, neuroscience, or a related field with an emphasis on perceptual modeling, audio machine learning psychoacoustics/physics, and/or metrics evaluating perceptual performance
  • Experience with MATLAB, R, Python, and/or C++
  • Knowledge of perceptual audio evaluation techniques, standard audio quality metrics, and deriving new metrics for audio applications


Facebook is proud to be an Equal Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law.Facebook is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@fb.com.