AIML - Machine Learning Manager - Responsible AI and Safety

In this role, you will lead a dedicated red-teaming team, building and running an independent program that actively probes Apple Intelligence features for safety and security risks, while upholding Apple's values, privacy, and quality standards.

Description

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 in 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 an inclusive culture of technical excellence, empower senior leadership with safety recommendations, and systematically remove roadblocks to ensure team success.

Minimum Qualifications

• 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

Preferred Qualifications

• Experience working in the Responsible AI space
• Publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, EMNLP, etc.)
• Experience working on Responsible AI and AI Safety
• Strong organizational and operational skills working with large, multi-functional, and diverse teams
• Curiosity about fairness and bias in generative AI systems, and a strong desire to help make the technology more equitable