Research Scientist Intern, Audio, Machine Learning and Computer Vision (PhD)
Job details
- Employment
- Internship
- Level
- Internship
- Experience
- 3+ years
- Education
- PhD
- Posted
- Oct 21, 2026
- Last confirmed open
- Oct 28, 2026
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Research Scientist Intern, Audio, Machine Learning and Computer Vision (PhD)
Research Scientist Intern, Audio, Machine Learning and Computer Vision (PhD)
Cambridge, UK
Research
+ 2 more
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The Meta Reality Labs Research Team brings together a world-class team of researchers, developers, and engineers to create the future of virtual and augmented reality, which together will become as universal and essential as smartphones and personal computers are today. And just as personal computers have done over the past 45 years, AR, VR and MR will ultimately change everything about how we work, play, and connect.
We are developing all the technologies needed to enable breakthrough AR glasses and VR headsets, including optics and displays, computer vision, audio, graphics, brain-computer interfaces, haptic interaction, eye/hand/face/body tracking, perception science, and true telepresence.
Some of those will advance much faster than others, but they all need to happen to enable AR, VR and MR that are so compelling that they become an integral part of our lives.
In particular, the Meta Reality Labs Research audio team is focused on two goals; creating virtual sounds that are perceptually indistinguishable from reality, and redefining human hearing. See more about our work here: https://tech.facebook.com/reality-labs .
These two initiatives will allow us to connect people by allowing them to feel together despite being physically apart, and allow them to converse in even the most difficult listening environments.
Meta Reality Labs Research is looking for experienced interns who are passionate about ground breaking research in audio signal processing, machine learning and audio visual learning to solve important audio-driven problems for AR/VR applications.
We currently have open positions for a range of projects in multimodal representation learning, audio visual scene analysis, egocentric audio visual learning, multi-sensory speech enhancement and acoustic activity localization.
Our internships are twelve (12) to twenty four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, Audio, Machine Learning and Computer Vision (PhD) Responsibilities
- Research, model, design, develop, and test novel audio and speech processing algorithms using machine learning, signal processing, and computer vision.
- Collaborate with researchers and engineers across diverse disciplines.
- Design and implementation of novel algorithms to solve audio research problems.
- Experimental design, implementation, and execution to evaluate new audio technologies.
- Collaboration with other researchers across audio and acoustic engineering disciplines.
- Communication of research agenda, progress, and results.
Minimum Qualifications
- Currently has, or is in the process of obtaining, a PhD degree in the field of Computer Science, Artificial Intelligence, Signal Processing, Machine Learning, Computer Vision, Electrical Engineering, Applied Math, Acoustics Engineering, Biomedical Engineering, or a related STEM field
- 3+ years experience with Python, Matlab, or similar
- 3+ years experience with machine learning software platforms such as PyTorch, TensorFlow, etc
- 2+ years experience building novel computational models in audio or audio-visual or speech application domains using machine learning or signal processing
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Preferred Qualifications
- Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. Github)
- Strong background in statistical modeling techniques, and/or signal processing
- Proven track record of achieving results as demonstrated in accepted papers at top computer vision and machine learning related conferences such as CVPR, ECCV, NIPS, ICASSP, InterSpeech etc
- Experience working and communicating cross functionally in a team environment
- Intent to return to a degree-program after the completion of the internship/co-op
About Meta
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world.
Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Equal Employment Opportunity
Meta is proud to be an Equal Employment Opportunity employer.
We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.
You may view our Equal Employment Opportunity notice here .
Meta is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, fill out the Accommodations request form .
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Equal Employment Opportunity Meta is proud to be an Equal Employment Opportunity employer.
We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable le