SummaryPosted: Jan 30, 2025Weekly Hours: 40 Role Number:200587346Product Operations partners with a variety of different engineering and operations teams, our team leads development of machine learning solutions. We deliver projects from end-to-end: problem statement and conceptualization, proof-of-concept, and participation in final deployment! You will also perform ad-hoc statistical analyses. You will also work closely with data engineers to generate detailed business intelligence solutions. You will be expected to conduct presentations of analyses to a wide range of audiences including executives.DescriptionDescriptionProduct Operations partners with a variety of different engineering and operations teams, our team leads development of machine learning solutions. We deliver projects from end-to-end: problem statement and conceptualization, proof-of-concept, and participation in final deployment! You will also perform ad-hoc statistical analyses. You will also work closely with data engineers to generate detailed business intelligence solutions. You will be expected to conduct presentations of analyses to a wide range of audiences including executives.Minimum QualificationsMinimum Qualifications3+ years experience in machine learning algorithms, software engineering, and data mining models with an emphasis on large language models (LLM) or large multimodal models (LMM).Masters in Machine Learning, Artificial intelligence, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering or related field.Key QualificationsKey QualificationsPreferred QualificationsPreferred QualificationsProven experience with LLM and LMM development, fine-tuning and application building. Experience with agents and agentic workflow is a major plus.Strong software development skills with proficiency in Python. Experienced user of ML and data science libraries. Experience of working with Kubernetes, DAG, docker, Conductor, etc. is a plus.Understand algorithms (be able to tweak them when needed) as well as infrastructure that enables fast iterations.Proven experience with transformer models such as BERT, GPT, etc., and a solid understanding of their underlying principles is a plus.Ability to meaningfully present results of analyses in a clear and impactful manner. Able to break down sophisticated machine learning model knowledges to digestible information for non-technical audience.Proven experience in managing and mentoring teams is a plus.Experience in applying ML techniques in manufacturing and testing space is a major plus.Education & 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 $214,500, 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.
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