ML Data - Research Scientist

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you could accomplish. Dynamic, smart people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same passion for innovation that goes into our products also applies to our practices, strengthening our commitment to leave the world better than we found it. Join us to help deliver the next groundbreaking Apple product.

Do you love working on challenges that no one has solved yet? As a member of our dynamic group, you will have the unique and rewarding opportunity to craft upcoming products that will delight and inspire millions of Apples customers every single day. When collecting multi-modal human data, establishing a reliable "ground truth" can be notoriously difficult and subjective. We are looking for an ML Data Researcher who will tackle this exact challenge. Your goal will be to design and conduct experiments on our data collection methods to discover techniques that reduce subjectivity, improve signal quality, and ultimately help our multi-modal models converge faster and achieve higher performance.Define research topics and data strategies aligned with model performance and product requirements Design, build, and run controlled experiments to evaluate how data collection methods, quality, and composition affect model convergence and downstream performance Design new ways to collect, label, and interpret multi-modal human data, translating insights into improved collection protocols and data specifications Design novel methods to collect, analyze, and interpret multi-modal human data, translating these insights into highly reliable "ground truth" specifications Characterize the practical and statistical limits of data collection setups (sensors, protocols, annotation pipelines) to inform feasibility and define data requirements Develop and analyze real-world data collection experiments (e.g., A/B tests on collection methodology, sampling strategy, labeling schemes) to support model training work Analyze and report results clearly, translating findings into actionable recommendations for data pipelines, labeling guidelines, and dataset design Partner with multidisciplinary teams across hardware, software, research, and ML engineering to drive data collection from concept to production-scaleBS in Computer Science, Machine Learning, Statistics, Neuroscience, or a closely related field Hands-on experience in a data-oriented, experimentation-heavy role, ideally supporting ML model developmentMS/PhD in Computer Science, Machine Learning, Statistics, Neuroscience, or a closely related field 3 years of relevant industry experience Experience with multi-modal human data (e.g., video, audio, motion capture) and the challenges of establishing ground truth for such data Familiarity with human probing/annotation methods and inter-rater reliability techniques Experience designing data collection experiments and interpreting their effect on model training/convergence Outstanding communicator with the ability to present complex technical findings to diverse audiences Collaborative team player who thrives in multidisciplinary, cross-functional environment