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 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 requirementsnDesign build and run controlled experiments to evaluate how data collection methods quality and composition affect model convergence and downstream performancenDesign new ways to collect label and interpret multi-modal human data translating insights into improved collection protocols and data specificationsnDesign novel methods to collect analyze and interpret multi-modal human data translating these insights into highly reliable ground truth specificationsnCharacterize the practical and statistical limits of data collection setups (sensors protocols annotation pipelines) to inform feasibility and define data requirementsnDevelop and analyze real-world data collection experiments (e.g. A/B tests on collection methodology sampling strategy labeling schemes) to support model training worknAnalyze and report results clearly translating findings into actionable recommendations for data pipelines labeling guidelines and dataset designnPartner with multidisciplinary teams across hardware software research and ML engineering to drive data collection from concept to production-scale

BS in Computer Science Machine Learning Statistics Neuroscience or a closely related fieldnHands-on experience in a data-oriented experimentation-heavy role ideally supporting ML model development

MS/PhD in Computer Science Machine Learning Statistics Neuroscience or a closely related fieldn3 years of relevant industry experiencenExperience with multi-modal human data (e.g. video audio motion capture) and the challenges of establishing ground truth for such datanFamiliarity with human probing/annotation methods and inter-rater reliability techniquesnExperience designing data collection experiments and interpreting their effect on model training/convergencenOutstanding communicator with the ability to present complex technical findings to diverse audiencesnCollaborative team player who thrives in multidisciplinary cross-functional environment