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Machine Learning Audio R & D Engineer Job at Apple Inc. in Cambridge

Machine Learning Audio R & D Engineer Job at Apple Inc. in Cambridge

MediabistroCambridge, MA, United States
2 days ago
Job type
  • Full-time
Job description

Cambridge, Massachusetts, United States Machine Learning and AI

The AMT Audio team is looking for a highly motivated and talented research and development machine learning engineer to develop models for speech and audio applications.The Audio and Media Technologies (AMT) is at the center of Apple’s innovative products, including the Mac, iPhone, iPad, Apple Watch, Apple TV, macOS, iOS, watchOS and tvOS. AMT’s Core Audio team provides audio foundation for various high profile features like Siri, phone calls, Face Time, media capture, playback, and API’s for third party developers to enrich our platforms. The team is looking for talented engineers who are passionate about building audio software products for millions of customers and care about overall user experience. You will be revolutionizing and contributing to future audio technologies.

Description As part of the audio team, you will develop machine learning models for speech enhancement, augmented hearing and hearing health applications. Train, fine-tune and compress models for production. Contribute to the team’s workflows building pipelines, writing datasets, and creating evaluation frameworks. Participate in cross-functional teams developing features and shipping products. Create intellectual property in the form of patents and publications.

Minimum Qualifications 4+ years experience in machine learning development, including audio and speech processing applications.

Practical and theoretical knowledge of machine learning architecture design and training / testing methodologies.

Experience building machine learning pipelines

Experience optimizing and compressing machine learning models for resource constrained platforms.

Excellent software architecture and programming skills in Python, C, C++

Knowledge of audio technologies

MS, in CS or EE, industry and research experience

Preferred Qualifications Experience developing models and algorithms for speech enhancement, source separation and assistive hearing

Demonstrated innovation in machine learning for audio (patents, publications)

Fundamentals of audio and speech signal processing

PhD, in CS or EE, Industry and research experience

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $162,500 and $286,400, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including : Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note : Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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.

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Machine Learning Engineer • Cambridge, MA, United States

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