Play a part in building the next revolution of machine learning technology. We're looking for a passionate researchers with team leadership experience to work on ambitious curiosity-driven long-term research projects that will impact the future of Apple, and our products. In this role, you'll have the opportunity to work on innovative foundational research in machine learning focusing on LLMs and generative models. As a leader of and active participant in the team, you will be inspired by a diversity of challenging problems, collaborate with world-class machine learning engineers and researchers, and publish your results in high-quality scientific venues. You have a strong research background in machine learning or related fields, and regularly publish your results in the main relevant conferences, and make sure that your research results are of high quality and reproducible. You will define your research plan to advance our understanding of machine learning and execute it through implementation and experimentation, in collaboration with your colleagues. You have experience mentoring researchers and the skills to guide complex research projects to meaningful conclusions, including preparing technical reports for publication and delivering conference talks. You will have the opportunity to collaborate with broader teams across Apple. PhD, or equivalent practical experience, in Computer Science, or related technical field Demonstrated expertise in machine learning research.\nAbility to formulate a research problem, design, experiment, implement and communicate solutions.\nPublication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, AISTATS, CVPR, ICCV, ECCV, ACL, EMNLP, etc).\nProven experience leading research teams and mentoring or managing researchers.\n Hands-on experience working with deep learning toolkits such as JAX, PyTorch or MLX\nStrong mathematical skills in differential calculus, probability, statistics.\nStrong coding skills, as exemplified by e.g. OSS contributions, and ability to maintain a coherent and evolving codebase.\nAbility to work as a team player in a diverse collaborative environment.\nYou have proposed through previous publications impactful methods in areas of interest to the group, such as generative modeling (flow matching, diffusion, etc.), LLM/VLM training/fine-tuning/inference, neural network theory, or scaling laws.