Machine Learning Engineering Manager, Responsible AI and Safety - AIML/SWE

Join Us in Shaping the Future of Generative AI at Apple

Are you passionate about building and leading teams that make AI systems safer, more inclusive, and globally representative? Apple is seeking an experienced Engineering Manager to lead a team shaping the future of responsible AI for the next generation of generative features.

In this role, you will lead a team of machine learning engineers driving the responsible AI lifecycle end-to-end: assessing risks, defining policies, developing mitigation strategies, and driving continuous improvements. You and your teams work will directly influence how we evaluate, align, and monitor the safety of large language and multimodal models.

As part of Apple's Responsible AI group within the Human-Centered Machine Intelligence (HCMI) organization, you'll collaborate with cross-functional partners to minimize unintended consequences across people, systems, and society while elevating feature capabilities and the overall user experience. You'll set technical direction, anticipate safety risks, and develop a team to deliver trusted, high‑quality AI experiences to users around the globe. We are seeking a visionary Machine Learning Engineering Leader to build, mentor, and develop a high-performing team driving Responsible AI efforts for global generative AI products. In this highly cross-functional role, you will partner with leadership, design, engineering, legal, and regulatory teams to define robust safety policies that align with product goals. You will provide critical technical direction for dataset design and safety alignment strategies, while directly overseeing the implementation of end-to-end mitigation architectures in production. Pre and Post-launch, you will remain hands-on-analyzing evaluation results, conducting failure investigations, and leveraging human and automated feedback to continuously improve feature safety and build user trust. As a champion for your team, you will foster a inclusive culture of technical excellence, empower senior leadership with safety recommendations, and systematically remove roadblocks to ensure team success.5+ years of experience in machine learning, including work with generative models (Transformers, LLMs, VLMs), NLP, or Computer Vision, with 2+ years directly managing engineering teams. Proven track record of leading technical teams through ambiguity to deliver high‑quality, high‑impact results. Proficiency in Python and data science libraries (e.g. Pandas) with strong skills in data analysis, visualization, and applied ML workflows. Excellent communication skills and proven ability to translate complex technical insights for cross‑functional partners, senior leadership, and executives. Strong analytical and independent problem-solving skills, with ability to guide teams through ambiguity. Familiarity interpreting outputs from human and automated evaluations, particularly with complex, nuanced, or multi‑labeled data, to inform mitigation improvements and shipping decisions. Experience collecting and analyzing language, vision, or multimodal datasets. Background in failure analysis, quality engineering, or robustness testing for ML‑driven systems. Comfortable leading a team that works with sensitive or potentially offensive content.BS, MS, or PhD in Computer Science, Machine Learning, or related field, or equivalent experience. Demonstrated success building and leading a team in a highly cross‑functional environment. Experience shipping complex AI systems at global scale. Background in model explainability or interpretability. Curiosity and research interest in fairness, bias, and the societal impacts of generative AI. Passion for building innovative, high‑impact products and teams that draw upon interdisciplinary skills.