Machine Learning Data Scientist

Summary Posted: Aug 22, 2024 Role Number: 200564796 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. This 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 improvement of foundation models, as well as refining the data used in training them, utilizing data centric AI approaches. Description Description Video Engineering DAQ team is seeking a self-motivated, detail-oriented data scientist to research and develop evaluation methods to drive the continuous improvement for Apple’s wide variety of computer vision projects. You will gain a deep understanding of various Apple algorithms and be tasked with performing deep-dive failure analysis on data from telemetry (on-device logging data) to large scale user studies to find potential root causes of unexpected algorithm performance, and you will routinely present your results to leadership and cross-functional teams. Moreover, a strong coding background will be required as you will also be tasked with developing and maintaining automation pipelines to analyze and visualize data. Minimum Qualifications Minimum Qualifications Minimum requirement of a bachelors degree. Background in data science, machine learning, computer vision and statistical data analysis. Programming skills in data manipulation & processing (SQL & Python preferred). Key Qualifications Key Qualifications Preferred Qualifications Preferred Qualifications Solid academic background in data science, machine learning, computer vision and statistical data analysis Experience in in-depth analysis of machine learning model failures Experience crafting, conducting, analyzing, and interpreting experiments and investigations Proven expertise in data wrangling and developing data visualizations & reporting with toolings such as Tableau, Superset, AWS etc. Diligent to keep track of and understand the workings of complex algorithms Self-motivated and curious with creative and critical thinking capabilities to improve data quality evaluation methods for diverse and complex data annotation programs Experience presenting data to collaborators Familiar with machine learning interpretability methods is a big plus Education & Experience Education & Experience Additional Requirements Additional Requirements Pay & Benefits 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 $58.61 and $88.29/hr, 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.