What are the responsibilities and job description for the AIML - Machine Learning and Applied Research, Responsible AI and Safety position at Apple, Inc.?
Apple Intelligence is designed as a deeply integrated, privacy-preserving capability that seamlessly enhances what people can do across iPhone, iPad, Mac, and other devices. Our goal is to elevate the user experience without requiring our customers to learn new products or fundamentally change how they interact with their technology.
Our team leads Responsible AI & Safety initiatives for global generative AI products, operating at the intersection of policy, product, and GenAI. We're seeking candidates who will shape safety policies in partnership with leadership, design, engineering, legal, and regulatory stakeholders-ensuring our safeguards advance both user protection and product innovation. \n\nYou will collaborate closely with top machine learning researchers and engineers, software engineers, and design teams to develop and deliver groundbreaking solutions for Apple products. We believe that the most exciting problems in machine learning research arise at the intersection of emerging technologies and real-world use cases. This is also where the most critical breakthroughs come from.\n\nYou will also work on producing safety evaluations that uphold Apple's Responsible AI values requires thoughtful data sampling, creation, and curation for evaluation datasets; high quality, detailed annotations and careful auto-grading to assess feature performance; and mindful analysis to understand what the evaluation means for the user experience.
3 years of proven ability in machine learning, including work with generative models (Transformers, LLMs, VLMs), NLP, or Computer Vision\n4 Years research or product deployment record in areas related to responsible AI, with publications in top ML venues (e.g., ACL, CHI, CVPR, EMNLP, FAccT, ICML, Interspeech, NeurIPS, UIST, etc.)\nStrong research fundamentals, machine learning principles, and development methodologies around LLMs, foundation models, and diffusion models\nExperience working with generative models for evaluation and/or product development, and up-to-date knowledge of common challenges and failures.\nPhD, MS or BS in Computer Science, Machine Learning, or related fields or an equivalent qualification acquired through other avenues
Experience working in the Responsible AI space.\nCuriosity about fairness and bias in generative AI systems, and a strong desire to help make the technology more equitable.\nProven success contributing in a highly cross-functional environment\nExperience shipping complex AI systems at global scale
Our team leads Responsible AI & Safety initiatives for global generative AI products, operating at the intersection of policy, product, and GenAI. We're seeking candidates who will shape safety policies in partnership with leadership, design, engineering, legal, and regulatory stakeholders-ensuring our safeguards advance both user protection and product innovation. \n\nYou will collaborate closely with top machine learning researchers and engineers, software engineers, and design teams to develop and deliver groundbreaking solutions for Apple products. We believe that the most exciting problems in machine learning research arise at the intersection of emerging technologies and real-world use cases. This is also where the most critical breakthroughs come from.\n\nYou will also work on producing safety evaluations that uphold Apple's Responsible AI values requires thoughtful data sampling, creation, and curation for evaluation datasets; high quality, detailed annotations and careful auto-grading to assess feature performance; and mindful analysis to understand what the evaluation means for the user experience.
3 years of proven ability in machine learning, including work with generative models (Transformers, LLMs, VLMs), NLP, or Computer Vision\n4 Years research or product deployment record in areas related to responsible AI, with publications in top ML venues (e.g., ACL, CHI, CVPR, EMNLP, FAccT, ICML, Interspeech, NeurIPS, UIST, etc.)\nStrong research fundamentals, machine learning principles, and development methodologies around LLMs, foundation models, and diffusion models\nExperience working with generative models for evaluation and/or product development, and up-to-date knowledge of common challenges and failures.\nPhD, MS or BS in Computer Science, Machine Learning, or related fields or an equivalent qualification acquired through other avenues
Experience working in the Responsible AI space.\nCuriosity about fairness and bias in generative AI systems, and a strong desire to help make the technology more equitable.\nProven success contributing in a highly cross-functional environment\nExperience shipping complex AI systems at global scale