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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 Apple's customers every single day.

Description

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.","responsibilities":"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-scale

Preferred Qualifications

MS/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

Minimum Qualifications

BS 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 development

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $225,300, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.