Machine Learning Engineer

Summary

Posted: Oct 30, 2024

Role Number:200576607

Imagine the impact you can make. A billion users will use the technologies you helped craft almost daily. At Apple, you will have the opportunity to work on products that are always leaders in the industry and potentially change the world! The Video Engineering team at Apple is responsible for creating the image and video core technologies used in almost all Apple products and services. With the recent surge of Generative AI models, there is an exciting opportunity to benefit from the power of generative models in video processing applications. We are looking for a highly self-motivated and enthusiastic individual with an advanced degree, who is able to excel in a technically challenging environment, to fill in the position of Machine Learning Engineer.

Description

We are looking for a Machine Learning Engineer who will join us to build Apple's next-generation video processing algorithms. In this role, you will identify and develop machine leaning models for solving specific video processing applications and work closely within a dynamic team to optimize and productize those features. Your responsibilities include, but not limited to: - Work on data collection and curation for training/testing/validation of machine learning models. - Investigate the latest deep learning based low-level vision methods. - Harness the power of generative and multi-modal foundation models in improving the quality of video features across Apple products.

Minimum Qualifications

• Masters degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields.
• Knowledge of the principles, algorithms, and techniques used in machine learning and computer vision with first-hand experiences.
• Programming skills and hands-on experience with Python and deep learning frameworks such as PyTorch.
• Hands on experience training large generative neural networks (GAN, Diffusion Models).

Preferred Qualifications

• PhD degree in Machine Learning, Computer Science, Electrical/Computer Engineering, or related fields.
• Knowledge of low-level vision algorithms such as spatial and temporal image/video scaling, noise reduction, etc.
• Background in digital signal and image processing
• Hands on experience with multi-modal foundation models
• Publication record in top-tier conferences (e.g., CVPR, ICCV, SIGGRAPH, ECCV, NeurIPS, ICML, ICLR).
• Excellent independent problem-solving skills
• Excellent written and oral communication skills

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 $143,100 and $264,200, 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.

More

• 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.