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Research Scientist Intern, Voice Modeling Team (PhD) London

Meta

Research Scientist Intern, Voice Modeling Team (PhD) London

Meta

London, United Kingdom

·

On-site

·

Internship

·

2w ago

Benefits & Perks

Equity

Equity

Required Skills

Python

C++

Machine learning

Deep learning

Speech technology

Meta was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Meta offers countless ways to make an impact in a fast growing organization.We are looking for Research Scientist Interns to join the Meta AI Speech team in London. Our team creates spoken language technologies to make it faster and easier for people to build community and connect with others around the world. We conduct product-motivated research in ML/AI and design, develop and deploy state-of-the-art algorithms to the rest of Meta. We work on all aspects of AI for speech and audio processing, including speech recognition, speech synthesis, and speech-text foundation models. Our work is largely focused on the areas of voice interfaces, including speech technologies for Ray-Ban | Meta Ray Ban smart glasses, Quest 3 mixed-reality headsets, Augmented Reality, the Metaverse, and understanding video on Facebook and Instagram, including transcription, translation, and content understanding.As a Research Scientist Intern, you will help us develop innovative models and algorithms and apply them to large-scale production speech tasks. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.

Research Scientist Intern, Voice Modeling Team (PhD) London Responsibilities:

  • Perform research to advance the science and technology of intelligent machines.
  • Develop novel and accurate speech algorithms and systems, leveraging Deep Learning and Machine Learning on big data resources.
  • Analyze and improve efficiency, scalability, and stability of various deployed systems.
  • Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
  • Publish research results and contribute to research that can be applied to Meta product development.

Minimum Qualifications:

  • Currently has or is in the process of obtaining a Ph.D. degree in Computer Science, Artificial Intelligence, Natural Language Processing, Speech Recognition, Sentiment Analysis, or relevant technical field
  • Must obtain work authorization in country of employment at the time of hire and maintain ongoing work authorization during employment
  • Experience in C/C++ and Python
  • Experience with deep learning frameworks such as Pytorch or Tensorflow
  • Research and/or work experience in machine learning, deep learning, and/or speech technology

Preferred Qualifications:

  • Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as NeurIPS, ICLR, AAAI, CVPR, ICML, ICASSP, Interspeech or similar
  • Experience working with other modalities such as vision and text understanding is a plus
  • Experienced with training deep neural networks for key Speech tasks such as speech recognition, speech synthesis, speech translation, speaker diarization, sentiment analysis, acoustic event recognition, scene understanding, wake word, etc
  • Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
  • Intent to return to degree program after the completion of the internship/co-op
  • A strong interest in theoretical and empirical research and for answering hard questions with research
  • Interpersonal experience: cross-group and cross-culture collaboration
  • Ability to stay in touch with the literature of a particular domain and has the ability to reproduce results if needed

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 Whats App 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.

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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About Meta

Meta

Meta

Public

A social technology company that enables people to connect, find communities, and grow businesses.

10,001+

Employees

Menlo Park

Headquarters

$800B

Valuation

Reviews

3.4

26 reviews

Work Life Balance

2.3

Compensation

4.2

Culture

2.8

Career

3.1

Management

2.1

45%

Recommend to a Friend

Pros

Excellent compensation and benefits

Smart and talented colleagues

Fast-paced and challenging work environment

Cons

Frequent layoffs and job insecurity

Poor leadership and management accountability

High stress and competitive work environment

Salary Ranges

40,175 data points

Mid/L4

Mid/L4 · Data Scientist

3,113 reports

$284,667

total / year

Base

$179,458

Stock

$79,981

Bonus

$25,228

$193,897

$434,902

Interview Experience

6 interviews

Difficulty

4.2

/ 5

Duration

21-35 weeks

Offer Rate

17%

Experience

Positive 17%

Neutral 17%

Negative 66%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Coding Interviews

6

System Design Interview

7

Behavioral Interview

8

Final Loop/Hiring Manager Round

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Live Coding