Want to work on cutting edge technology that keeps the customer front and center? The Video Engineering group at Apple is responsible for creating the image/video core technologies used in almost all Apple products and services. As a machine learning engineer, you'll be developing machine learning based technologies for the image and video domain. As a member of a fast-paced team, you will also have the unique and exciting opportunity to shape upcoming products that have direct customer impact and will delight and inspire millions of people every day!

Description

This role requires an independent, self-motivated, and creative engineer with deep expertise in machine learning, coupled with a strong understanding of video and image processing quality. Your primary focus will be applying cutting-edge machine learning techniques to complex image and video challenges to create customer impact across current and future Apple products. In this role, you'll work both independently and collaboratively with team members to prototype innovative deep learning applications for video processing, presenting and demonstrating your work to cross-functional teams and leadership alike. You'll be responsible for designing sophisticated model architectures, fine-tuning performance parameters, and implementing architectural modifications to enhance overall output quality. Working closely with the team, you'll focus on seamlessly porting solutions across different platforms while optimizing models for memory efficiency, power consumption, and processing speed to balance quality in operating constraints. Additionally, you'll strategically distribute computational workloads across CPU, GPU, Apple Neural Engine, and other specialized hardware components to develop robust, viable solutions.

Preferred Qualifications

Master degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields.

Experience in prototyping models for edge devices through quick iterations.

Familiarity with productization flow for ML models.

Prior experience working on deep learning techniques for video processing / computer vision.

Strong fundamentals in Computer architecture.

Good written and oral interpersonal skills

Minimum Qualifications

Bachelor's degree in Computer Science, Electrical/Computer Engineering, or a related field.

Excellent fundamentals in machine learning.

Knowledge of Video or Image processing or Computer Vision.

Solid programming skills for common ML frameworks like Py Torch or Tensor Flow.

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 .

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 $126,800 and $190,900, 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.