The Apple Services GenAI & ML Frameworks team focuses on integrating foundation model capabilities with real-world production systems. This role involves continual pretraining, post-training, and optimization of large language models (LLMs) while collaborating with various teams to enhance domain knowledge and system integration. The ideal candidate will lead initiatives from problem definition to execution, ensuring the transition of LLM research into practical applications. A strong emphasis is placed on improving research velocity and production readiness.

• BS/MS or PhD in a quantitative field such as Computer Science, Maths, Statistics, or Physics.
• Proficient programming skills in Python.
• Hands-on experience with deep learning toolkits like Jax, TensorFlow, or PyTorch.
• Proven track record in training or deploying large models or building large-scale distributed systems.
• Deep understanding of Deep Learning and Large Language Models (LLMs).
• Experience in Natural Language Processing.

• Operate end-to-end across model development and production integration.
• Improve LLM domain knowledge, tool use, reasoning, and system integration.
• Collaborate closely with product, infra, and foundation model teams.
• Lead ambiguous cross-LOB initiatives from problem definition through execution and scaling.
• Build robust tooling around synthetic data generation, evaluation, and training pipelines for LLMs.

• 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.