The ML Research Engineer role at Apple focuses on building a scientific foundation for evaluating AI systems, particularly in the context of large language models and human-AI interaction. This interdisciplinary team combines expertise from measurement science, machine learning research, and platform engineering. The position requires a blend of research and engineering skills to prototype and implement evaluation methodologies at scale. Candidates should be passionate about advancing AI evaluation and comfortable navigating both research and production environments.

• Bachelor's degree in Computer Science, Machine Learning, Software Engineering, or a closely related field; Master's preferred.
• 2+ years of hands-on experience in a role combining machine learning and software engineering.
• Strong proficiency in Python and the modern ML ecosystem, including PyTorch, JAX, or TensorFlow.
• Solid software engineering fundamentals, including clean code design, version control, testing, debugging, and performance optimization.
• Experience working with large language models, including fine-tuning and building LLM-powered applications.
• Demonstrated ability to work across the research-to-production spectrum.
• Practical experience with cloud-native development and deployment, including containerization and CI/CD pipelines.
• Strong communication skills and comfort working in interdisciplinary teams.
• Comfort with ambiguity and new problem spaces.
• Master's or Ph.D. in Computer Science, Machine Learning, or a related field.

• Partner with scientists to rapidly prototype their ideas and implement methods from recent papers.
• Run large-scale experiments and provide critical feedback based on engineering experience.
• Collaborate with platform engineers to transition research prototypes into production.
• Ensure that experimental or prototype code is made robust, scalable, and usable by others.
• Engage productively with both researchers and platform engineers to facilitate interdisciplinary collaboration.
• Contribute to the evaluation of AI systems using evaluation-specific methods and frameworks.
• Help define technical direction and engineering culture within fast-moving, early-stage teams.

• 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.