Machine Learning Engineer- GenAI

Apple Inc.; San Diego (CA); On-site; USD 150,400 - 277,600; Full time

Benefits offered by this job

Stock programs

Relocation assistance

Tuition reimbursement

Employee stock purchase plan

Job summary

Apple Inc. seeks an extraordinary engineer to join the Product Operations team to design and implement machine learning strategies for the supply chain and smarter factories. You will work with cross-functional teams on large-scale data and deploy end-to-end ML solutions.

Minimum qualifications include 3+ years in GenAI/ML with a Masters in related field. Preferred skills cover LLM/LMM development, LangChain, and Kubernetes-based environments. Eligible for relocation and stock programs.

Qualifications

• 3+ years in GenAI, ML, software eng, or data mining with focus on LLM/LMM.
• Masters in AI/ML/CS or related field.

Responsibilities

• Lead end-to-end ML projects from problem statement to deployment.
• Collaborate with data engineers to build BI solutions for supply chain.
• Present analyses to executives and non-technical audiences.

Skills

GenAI applications

LLM/LMM concepts

Data mining

Education

Master's in AI/ML/CS/Statistics

Tools

Kubernetes

Docker

Apache Airflow

Ray

LangChain

LlamaIndex

Job description

Cupertino, California, United States Operations and Supply Chain

Imagine what you could do here. At Apple, we believe new insights have a way of becoming excellent products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry‑leading environmental efforts. Join Apple, and help us leave the world better than we found it. It takes deeply dedicated, intelligent individuals to maintain and exceed the high expectations at Apple. The Product Operations team is looking for an extraordinary engineer to join our team. You will help design and implement our machine learning strategy to the substantial supply chain and help build the future of our manufacturing systems and smarter factories. We will be collaborating and working with multi‑functional teams and applying algorithms to large‑scale data.

Description

Product 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 Qualifications

• 3+ years experience in GenAI applications, machine learning algorithms, software engineering, and data mining models with an emphasis on large language models (LLM) or large multimodal models (LMM).
• Masters in Artificial intelligence, Machine Learning, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering or related field.

Preferred Qualifications

• Proven experience in GenAI application building with agents and agentic workflows. Experience with LLM and LMM development and fine‑tuning is a major plus.
• Proficiency in using cutting‑edge GenAI tools, i.e. Claude Code, Roo Code, etc.
• Familiarity with distributed computing, cloud infrastructure, and orchestration tools, such as Kubernetes, Apache Airflow (DAG), Docker, Conductor, Ray for LLM training and inference at scale is a plus.
• Hands‑on experience with LangChain and LlamaIndex, enabling RAG applications and LLM orchestration.
• Deep understanding of transformer‑based architectures (e.g., BERT, GPT, LLaMA) and their optimization for low‑latency inference.
• Ability to meaningfully present results of analyses in a clear and impactful manner, breaking down complex ML/LLM concepts for non‑technical audiences.
• Experience applying ML techniques in manufacturing, testing, or hardware optimization is a major plus.
• Proven experience in leading and mentoring teams is a plus.

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 $277,600, 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.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace

Learn about reasonable accommodations for job applicants

Apple accepts applications to this posting on an ongoing basis.