This role involves contributing to the development of the next generation of generative AI applications at Apple. The team is focused on researching and advancing red teaming methods for large language models (LLMs) and diffusion models. The position requires expertise in machine learning research and production deployment, with an emphasis on ensuring the safe deployment of LLMs in Apple products. Candidates will work collaboratively in a diverse environment to tackle ambitious projects that will shape the future of Apple's offerings.

• PhD or equivalent experience in Computer Science or a related technical field.
• Demonstrated expertise in machine learning research and/or production deployment lifecycle.
• Deep understanding of large language models.
• Hands-on experience with deep learning toolkits such as TensorFlow or PyTorch.
• Publication record in relevant conferences such as NeurIPS, ICML, ICLR, or EMNLP.
• Experience working on Responsible AI and AI Safety.

• Research and advance red teaming methods for LLMs and diffusion models.
• Develop mitigations and safeguards to ensure the safe deployment of LLMs in Apple products.
• Create tools, metrics, and datasets for assessing and evaluating the safety of LLMs throughout the model deployment lifecycle.
• Develop methods and tools to interpret and explain failures in language models.
• Formulate research problems, design experiments, and implement solutions.

• 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.