Senior ML Data Engineer, MLO

Do you believe Machine Learning and AI can change the world? We truly believe it can! We are the ML Data Team of the Intelligent System Experience (ISE) group at Apple. We are responsible for building high quality datasets at scale. Every year, our team produces datasets used in the training of ML and AI-centric features for many Apple products, including iPhone, iPad, Mac, Apple Watch and even AirPods. Our work is used in very visible and critical features, from the wallpaper on your iPhone Lock Screen, to your personalized stickers on iMessage, to Apple Intelligence features such as on-device Genmoji and other visual generative models, to the models that highlight the faces and memories of your loved ones in your Photos app. We’re looking for an exceptional software & data engineer who is passionate about Apple products and values, who has a passion for data operations at scale, is comfortable in a fast paced environment and who is committed to the hard work necessary to continuously improve our ML data pipelines. We invite you to join us at this exciting time. Grow fast and positively impact multiple critical features from your first day at Apple! Our team focuses on acquiring, synthesizing, annotating, and ensuring the quality of ML data, driving numerous features in collaboration with R&D teams in Apple’s SWE organization. Minimum Qualifications: 7 years of industry experience as a data engineer serving various ML applications (vision domain preferred) Bachelor's degree in Computer Science or related field Preferred Qualifications: Proven experience designing, automating and scaling large data pipelines (petabyte scale desired) using state of the art processing technologies (eg familiarity with Iceberg, BigQuery, Airflow, Spark, etc.) Expertise in Python, Go or another modern programming language; you are expected to produce high quality, efficient code and participate in code reviews Strong ability to design and lead a technical roadmap, work with cross functional teams and a diversity of profiles, proven capacity to influence and build alignment Demonstrated prior experience in delivering large scale multimodal datasets for foundation models Self-starter, able to handle ambiguity, comfortable in a fast-pace environment, identify risks, mitigate, and autonomously find the right people and tools to get the job done Proven track record of mentoring and growing engineers, lift the level of software engineering excellence in a ML data ops team typically focused on short term deliveries