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Machine Learning Engineer

Yesterday Cupertino, CA

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Description

APPLE INC has the following available in Cupertino, California and various unanticipated locations throughout the USA. Design, implement, extend, and refactor machine learning inference system frameworks to streamline the deployment, execution, and evaluation of ML models. Design and implement lowlatency inference solutions tailored to specific use cases and deployment environments, ensuring real-time responsiveness and scalability under varying workloads. Develop, expand, and improve text input features on Apple's platforms by leveraging machine learning models and scalable, performant ML-driven architectures. Lead the deployment and delivery of machine learning models across various architectures, including cloud-based and embedded systems, and design system appropriate architectures for optimal reliability and performance. Collaborate with ML modeling experts, data scientists, and software developers to understand requirements, prioritize initiatives, and drive alignment towards shared goals. Design and implement evaluation techniques to test features. Debug failures during feature and interoperability testing. Process data, train, evaluate, and deploy machine learning models to classify text. 40 hours/week. 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 $187,741 - $272,100/yr and your base pay will depend on your skills, qualifications, experience, and location.

PAY & BENEFITS: 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: https://www.apple.com/careers/us/benefits.html.

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

Preferred Qualifications

N/A

Minimum Qualifications

Master's degree or foreign equivalent in Computer Science, Networked Systems, or related field and 2 years of experience in the job offered or related occupation.

1 year of experience with each of the following skills is required:

Using compiled object-oriented programming languages including C++ or C#.

Utilizing scripting languages, including Python.

Software system design principles and best practices.

Deploying and optimizing ML models across various platforms for varying workloads.

System architecture design for cloud-based and embedded environments.

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Debugging complex issues in ML systems and ensuring system interoperability.

Unit testing and automated testing solutions for ML-driven features.

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 .

Client-provided location(s): Cupertino, CA
Job ID: apple-200652083-0836_rxr-662
Employment Type: OTHER
Posted: 2026-03-30T19:40:04

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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