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Video Machine Learning Engineer

Video Machine Learning Engineer

MediabistroCupertino, CA, United States
15 days ago
Job type
  • Full-time
Job description

Overview Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something – you’ll add something. We are looking for a talent who will join us to craft the future of video coding and processing. Our team develops cutting edge machine learning technologies and systems that enable intelligent and interactive video experience in Apple’s products, such as FaceTime, Camera, AirPlay, CarPlay, Screen Share, Immersive Reality, etc. You will work closely with a group of highly motivated specialists to develop exciting machine learning technologies that will make a huge impact to customers.

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Description

Description

As a video machine learning engineer in our team, you will be responsible for developing ML / DL solutions to enhance or bring new user experiences. You will be deeply involved in developing new or improving existing algorithms; designing neural network architectures; training, optimizing, integrating networks; and coordinating with various teams to ship new technology in Apple products.

Responsibilities

Design neural network architectures

Train, optimize, and integrate neural networks

Participate in developing new or improving existing algorithms

Enhance or come up with new user experiences to video communication

Coordinate with various teams to develop and ship new technology

Minimum Qualifications

Master’s degree in Electrical Engineering or Computer Science or 3 years of equivalent work experience

Experience in digital video processing

Deep knowledge and experience in designing and optimizing neural networks

Preferred Qualifications

Strong programming, problem solving, and performance optimization skills

Modern video codec knowledge is a plus

Pay & Benefits 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 $147,400 and $272,100, 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 • Cupertino, CA, United States

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