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AIML Resident - ASR Modeling

AT Apple
Apple

AIML Resident - ASR Modeling

Cambridge, MA

Summary

Posted: Oct 23, 2024

Role Number:200574855

Imagine what you could do here! At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Combining groundbreaking machine learning research with next-generation hardware, our teams take user experiences to the next level!

Description

Apple's AIML residency is a year-long program inviting experts in various fields to apply their own domain expertise to innovate and build revolutionary machine learning and AI-based products and experiences. As AI-based solutions spread across disciplines, the need for domain experts to understand machine learning and apply their expertise in ML settings grows. Residents will have the opportunity to attend ML and AI courses, learn from an Apple mentor closely involved in their program, collaborate with fellow residents, gain hands-on experience working on high-impact projects, publish in premier academic conferences, and partner with Apple teams across hardware, software, and services. The Automatic Speech Recognition (ASR) Modeling Team has been crafting and initiating major speech model changes over the years. We've grown on-device accuracy and private speech recognition to all major markets (40+ locales) and across various hardware platforms; each with diverse compute restrictions. Our team enables prominent product experiences featured in various WWDC announcements, such as Vision Pro and Apple Intelligence. Our groundbreaking research environment is grounded in Apple specific production needs. Residents will use large amounts of data, develop and extend pioneering algorithms, address both general ML problems and challenges specific to the speech modality, in order to address varying speech recognition needs - with the accuracy, privacy, efficiency crucial to Apple products. You'll work daily with experienced mentors who've successfully advised colleagues like you. Residents will receive support to formulate innovative research problems, perform systematic experimentation, and influence how diverse sets of voice experiences are powered by speech recognition. You'll also benefit from the team's rich experience shipping technologies used broadly in Apple's products and could publish in top venues in the machine learning and speech and language technology community.

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Minimum Qualifications

  • Proficiency in a programming language such as Python, Objective-C, C++, Swift, and/or R. Candidates should have experience completing a moderate-sized software project
  • Demonstrated ability to connect and collaborate with others
  • Graduate degree in a STEM field or equivalent industry experience in software engineering
  • Apple's AIML residency is a one-year program starting in July 2025. Residents must be available to work full-time (40 hours/week) July 14, 2025 - July 10, 2026

Preferred Qualifications

  • Ideal candidates will also have academic, research, or industry experience in at least one of the following: Electrical Engineering, Signal Processing, Machine Learning & ML Research, or Natural Language Processing/Speech/Conversational AI. Thesis, capstone project, internship, co-op, and/or proven experience in these fields qualifies
  • We encourage you to submit a cover letter as part of your application explaining: What are your research interests? How do they apply to the specific Residency position you applied to? Why would you would like to join the AIML residency program broadly?
  • APPLICATION DEADLINE: DECEMBER 16, 2024

Additional Requirements

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  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

Client-provided location(s): Cambridge, MA, USA
Job ID: apple-200574855-1
Employment Type: Full Time

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