Engineering Manager, Data for Applied AI Models

We are seeking a deeply technical manager to lead our Data team. You will be responsible for understanding and drafting requirements, developing annotation tools and workflows, and managing the delivery and quality of data. The Data team is an immediate partner to our applied ML team, jointly responsible for developing and shipping production models at Apple scale. The huge importance of data on product quality makes this a high-impact role — your deliverables will be used to train and evaluate the models we ship. You will use a mix of human annotation and generative AI techniques to deliver high-quality data for each task. You’ll collaborate closely with researchers, software engineers, and product teams to move ideas from prototypes to production. This includes innovative ways to produce scalable, efficient, and accurate data pipelines that leverage the latest AI has to offer. In this role, you will manage, lead, and inspire a team of highly talented and experienced engineers. You will have strong technical, communication, and people management skills and be responsible for the team’s technical direction and execution. Our team values rapid iteration and delivering impactful results. The ideal candidate will have a passion for detail, getting things done, and delivering high-quality outcomes. Minimum Qualifications Master’s or PhD in Computer Science, Machine Learning Engineering, or equivalent professional experience. 5+ years of hands-on industry experience and a proven track record of shipping ML-powered products or features, ideally involving LLMs. Extensive experience with the ML development loop with a focus on data and annotations. Strong leadership and team management skills, as a manager or tech-lead manager. Proficiency in Python. Excellent communication, interpersonal, and presentation skills. Preferred Qualifications Experience creating data for multi-modal foundation models that integrate text, vision and/or audio. Experience developing AI agents capable of planning and tool use tasks using generative AI techniques. Experience developing ML systems for natural language understanding, visual understanding or digital assistants. Understanding of the latest generative AI development techniques.