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Machine Learning Video Algorithm Engineer

Yesterday San Diego, CA

The codec deep video processing team develops machine learning algorithms to power Apple technologies with the best user visual experience. In this role, you will work closely with company-wide multiple teams and in multiple projects, from data curation to model development, in a large-scale, to help deliver new features for Apple products and bring high impact to millions of users.

Description

Join us as a Machine Learning Engineer and build the next-generation video processing features. You will play the key role from data to feature development. In this role, you will identify and develop machine leaning solutions and work closely with multiple teams to optimize and productize those features.","responsibilities":"Design and develop data curation pipeline for pre-training and post-training.

Design and implement deep learning algorithms for video related tasks.

Design test suite and evaluation pipeline for validation and testing.

Optimize models and algorithms for performance, including latency, memory, and computational efficiency.

Integrate solutions into end-to-end video processing pipelines.

Preferred Qualifications

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

Knowledge of low-level vision algorithms including spatial and temporal image/video processing.

Experience working with multimodal and multimodal large language models (MLLMs) (e.g., image-text, video-audio systems).

Experience evaluating generative and multimodal models, including benchmarking and quality assessment.

Publication record in top-tier conferences (e.g., CVPR, ICCV, SIGGRAPH, ECCV, NeurIPS, ICML, ICLR)

Strong communication skills and documentation skills.

Minimum Qualifications

BS and a minimum of 3 years relevant industry experience.

Experience evaluating supervised, unsupervised, and deep learning models.

Proficiency in Python and libraries such as NumPy, pandas, scikit-learn, PyTorch, or TensorFlow.

Knowledge of the principles, algorithms, and techniques used in machine learning and video processing with first-hand experiences.

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 $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location.

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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.

Client-provided location(s): San Diego, CA
Job ID: apple-200649940-3543_rxr-662
Employment Type: OTHER
Posted: 2026-03-14T19:46:57

Perks and Benefits

  • Health and Wellness

    • Parental Benefits

      • Work Flexibility

        • Office Life and Perks

          • Vacation and Time Off

            • Financial and Retirement

              • Professional Development

                • Diversity and Inclusion

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