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Research Scientist Intern, Ultra-Low Power Audio Processing System (PhD)

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Meta

19d ago

  • Internship
    Full-time
    Off-cycle Internship
  • Software Engineering
    Engineering
  • Sunnyvale

AI generated summary

  • You must have work authorization, be pursuing a PhD in a related field, and have experience in low-power SoC design and machine learning/deep learning frameworks.
  • You will lead research in low power circuits, collaborate on architectures, evaluate performance, support cross-functional teams, and communicate findings internally and externally.

Requirements

  • Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
  • Currently has, or is in the process of obtaining, a PhD degree in Electrical or Computer Engineering, Computer Science or related field.
  • Experience in the architecture and design of digital SoC or analog/mixed-signal processing circuits using low-power techniques and industry-standard EDA tools.
  • 1+ years experience in developing solutions using machine learning and/or deep learning frameworks.

Responsibilities

  • Own a research project in the field of low power integrated circuits and systems for signal processing and machine learning applications.
  • Work with Silicon research teams to develop new architectures, run internal workloads and research design techniques.
  • Evaluate, prototype and estimate performance benefits of proposed techniques.
  • Collaborate with and support other researchers across various disciplines.
  • Work with cross-functional teams to enable new user experiences in AR/VR via innovative system-level experiments.
  • Contribute to execution of our silicon technology / compute roadmap to make advances in performance, power consumption and form factor.
  • Communication of research agenda, progress and results, both internally and externally.

FAQs

What is the duration of the internship?

The internship lasts between twelve (12) to twenty-four (24) weeks.

What fields of study should candidates be pursuing for this internship?

Candidates should be pursuing a PhD degree in Electrical or Computer Engineering, Computer Science, or a related field.

Is prior experience with machine learning frameworks required?

Yes, candidates should have at least 1+ years of experience in developing solutions using machine learning and/or deep learning frameworks.

What kind of projects will interns work on?

Interns will own research projects in the field of low power integrated circuits and systems for signal processing and machine learning applications.

Are there any specific qualifications preferred for this internship?

Preferred qualifications include experience in signal processing for voice and speech recognition, familiarity with MEMS microphone sensors, and a proven track record of significant results through publications or patents.

Will this internship require collaboration with others?

Yes, interns will collaborate and support other researchers across various disciplines and work with cross-functional teams.

How is compensation determined for this internship?

Compensation is determined by skills, qualifications, experience, and location, with a salary range of $7,313/month to $11,333/month along with benefits.

Is work authorization required for this internship?

Yes, candidates must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during their employment.

Does Meta provide any accommodations for candidates with disabilities?

Yes, Meta is committed to providing reasonable accommodations for candidates with disabilities in the recruiting process.

What kind of technologies will interns be working with?

Interns will be exploring new circuit design techniques, architectures, and technologies for future AR products, focusing on ultra-low power audio processing systems.

Meta

Technology
Industry
10,001+
Employees
2004
Founded Year

Mission & Purpose

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.