Facebook
Research Scientist Intern, Audio (PhD)
Facebook, Redmond, Washington, United States, 98052
Summary:
The XR Audio team at Meta is helping people around the world come together and connect through world-class Augmented and Virtual Reality hardware and software. We are developing the future of AR and VR, bringing products to consumers that transform entertainment and social experiences. These roles are focused on developing the next generation of speech and audio enhancement algorithms for wearables in various acoustic environments. Our team is a multi-disciplinary group with expertise in digital signal processing, machine learning, wireless systems, software architecture and distributed systems, and simulation/modeling, sound synthesis, music, audio and speech compression, and much more. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Required Skills:
Research Scientist Intern, Audio (PhD) Responsibilities:
Research, model, design, develop and test novel audio and speech processing algorithms using a combination of machine learning and signal processing to tackle unsolved real-world problems and push the state of the art in audio and advance AR/VR experiences.
Lead and contribute to cutting-edge AI model research that leads to publications on top-tier Audio/ML conferences.
Independently design and implement algorithms, train advanced AI models on large datasets, and evaluate their performance.
Develop novel deep learning techniques to achieve state-of-the-art accuracy within the constraints of on-device and real-time execution.
Collaborate with other research scientists and software engineers to develop innovative deep learning techniques for audio use-cases.
Communicate the experimental results and the recommendations clearly, both within the group as well as to the cross-functional groups.
Minimum Qualifications:
Currently in the process of obtaining a PhD in the field of Artificial Intelligence or related field.
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
Research experience in one or more of these areas: machine learning, deep learning, audio/speech processing, ML model compression, or related fields.
Experience building novel computational models in audio or speech application domains using machine learning and/or signal processing.
Experience with Python/shell scripts/Matlab/C/C++ or similar.
Experience working with machine learning libraries such as Pytorch, Tensorflow.
Preferred Qualifications:
Intent to return to degree-program after the completion of the internship.
Proven track record of publications at ICASSP, Interspeech, WASPAA, IWAENC, IEEE TASLP, Neurips or similar.
Demonstrated software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. Github).
Experience solving complex problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward.
Experience working and communicating cross-functionally in a team environment.
Strong background in one or more areas in Machine Learning such as: 1) Experience with developing scalable machine learning models that can evolve with newer device generations with minimal additional data, 2) Experience with techniques for model compression and/or deploying ML models on MIPS/Memory/Power constrained devices, 3) Experience with large scale model training, implementing algorithms, and evaluating performance with objective or subjective audio metrics.
Deep subject matter expertise in one or more areas in speech/audio signal processing such as: 1) Audio playback signal processing algorithms (such as compressors, limiters, EQs), 2) Adaptive system identification, noise reduction, sound source localization, beamforming, adaptive filters (such as echo/feedback cancellation), 3) Spatial audio and room acoustics.
Public Compensation:
$7,800/month to $11,293/month + benefits.
Industry:
Internet
Equal Opportunity:
Meta is proud to be an Equal Employment 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. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta 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 .
#J-18808-Ljbffr
The XR Audio team at Meta is helping people around the world come together and connect through world-class Augmented and Virtual Reality hardware and software. We are developing the future of AR and VR, bringing products to consumers that transform entertainment and social experiences. These roles are focused on developing the next generation of speech and audio enhancement algorithms for wearables in various acoustic environments. Our team is a multi-disciplinary group with expertise in digital signal processing, machine learning, wireless systems, software architecture and distributed systems, and simulation/modeling, sound synthesis, music, audio and speech compression, and much more. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Required Skills:
Research Scientist Intern, Audio (PhD) Responsibilities:
Research, model, design, develop and test novel audio and speech processing algorithms using a combination of machine learning and signal processing to tackle unsolved real-world problems and push the state of the art in audio and advance AR/VR experiences.
Lead and contribute to cutting-edge AI model research that leads to publications on top-tier Audio/ML conferences.
Independently design and implement algorithms, train advanced AI models on large datasets, and evaluate their performance.
Develop novel deep learning techniques to achieve state-of-the-art accuracy within the constraints of on-device and real-time execution.
Collaborate with other research scientists and software engineers to develop innovative deep learning techniques for audio use-cases.
Communicate the experimental results and the recommendations clearly, both within the group as well as to the cross-functional groups.
Minimum Qualifications:
Currently in the process of obtaining a PhD in the field of Artificial Intelligence or related field.
Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
Research experience in one or more of these areas: machine learning, deep learning, audio/speech processing, ML model compression, or related fields.
Experience building novel computational models in audio or speech application domains using machine learning and/or signal processing.
Experience with Python/shell scripts/Matlab/C/C++ or similar.
Experience working with machine learning libraries such as Pytorch, Tensorflow.
Preferred Qualifications:
Intent to return to degree-program after the completion of the internship.
Proven track record of publications at ICASSP, Interspeech, WASPAA, IWAENC, IEEE TASLP, Neurips or similar.
Demonstrated software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. Github).
Experience solving complex problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward.
Experience working and communicating cross-functionally in a team environment.
Strong background in one or more areas in Machine Learning such as: 1) Experience with developing scalable machine learning models that can evolve with newer device generations with minimal additional data, 2) Experience with techniques for model compression and/or deploying ML models on MIPS/Memory/Power constrained devices, 3) Experience with large scale model training, implementing algorithms, and evaluating performance with objective or subjective audio metrics.
Deep subject matter expertise in one or more areas in speech/audio signal processing such as: 1) Audio playback signal processing algorithms (such as compressors, limiters, EQs), 2) Adaptive system identification, noise reduction, sound source localization, beamforming, adaptive filters (such as echo/feedback cancellation), 3) Spatial audio and room acoustics.
Public Compensation:
$7,800/month to $11,293/month + benefits.
Industry:
Internet
Equal Opportunity:
Meta is proud to be an Equal Employment 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. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta 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 .
#J-18808-Ljbffr