Machine Learning Engineer - Integration

Job Description

Join our team as a Machine Learning Integration Engineer to build efficient deployment pipelines for ML models across Apple products.

Requirements

• MS in Computer Science or related field with focus on machine learning, computer vision, software engineering or similar.
• 3+ years experience in efficient deployment of ML models in production environments.
• Experience with ML frameworks (Core ML, PyTorch).
• Strong understanding of software engineering principles, version control, and CI/CD practices.
• Experience working with large, distributed codebases and multi-functional teams.
• Proficiency in Swift, Python, C++, Objective-C.

Responsibilities

• Design, implement, and maintain efficient ML model deployment pipelines across Apple products.
• Optimize model performance for diverse hardware configurations across Apple Silicon.
• Build and maintain MLOps infrastructure supporting continuous integration and deployment.
• Collaborate with ML researchers to transition models from experimentation to production.
• Develop APIs and SDKs for seamless ML model consumption.
• Profile and optimize model inference performance, memory usage, and battery efficiency.
• Implement error handling, fallback mechanisms, and monitoring systems.
• Collaborate with QA teams to establish testing strategies for ML-integrated features.
• Develop apps / dashboards for debugging and live assessment.

Benefits

• Employees at Apple are often offered comprehensive benefits that support physical and mental well-being—flexible medical plans, confidential counseling, onsite wellness centers at major campuses, and resources for fitness and daily life. Families typically receive fertility support, paid parental leave with gradual return, caregiving leave, and dependent-care guidance, while financial perks commonly include stock grants (with purchase discounts), 401(k) matching, and income-protection coverage. Employees also see robust time off, Apple University learning and tuition reimbursement, donation matching and paid volunteer hours, and deep product and partner discounts.