SummaryPosted: Oct 10, 2024Role Number:200572504Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something. Do you have a passion for computer vision and deep learning problems? Are you interested in the latest development of the multi-modal models? The Data Analytic and Quality (DAQ) group is seeking a Machine Learning/Data Scientist to specialize in the evaluation of multimodal foundation models.DescriptionDescriptionThis role involves collaboration with teams at Apple focused on developing foundation models, including ML engineers, data scientists, and ML infrastructure engineers. Your primary responsibilities will include developing methods for the evaluation and enhancement of foundation models, conduct thorough failure analysis on large multimodal models, develop tools for analyzing and visualizing data, design and implement experiment (DOE) for engineering studies and large scale user studies as well as contribute in defining feature specifications and anticipated user experience based on data insights.Minimum QualificationsMinimum QualificationsBS and a minimum of 3 years relevant industry experience3+ years of experience with significant experience in large-scale data analyticSolid foundation in data science, deep learning and statisticsDemonstrated experience in in-depth analysis of machine learning model failuresFamiliarity with various foundation models, such as SAM, LLAMA, LLaVA, CGPT4V, CLIPProficiency in PythonKey QualificationsKey QualificationsPreferred QualificationsPreferred Qualifications5+ years of experience with significant experience in large-scale data analyticsDeep expertise in data and model evaluationProficiency in Data Centric AIExperience with analytical tools such as Jupyter, Pandas, NumPy, MatplotlibExperience in training models using frameworks like PyTorch, TensorFlow, Jax, etcGood verbal and written communication skillsEducation & ExperienceEducation & ExperienceAdditional RequirementsAdditional RequirementsPay & BenefitsPay & BenefitsAt 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 $143,100 and $264,200, 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.
More

Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.