Job Detail

Machine Learning Engineer - LLM

Data Science and AI Full–time
ID: #19676
Posted: 2026-03-10
Salary

Description

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary 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. Description We are seeking a highly capable and dynamic Machine Learning Engineer to work cross-functional in building out a GenAI system in support of Beats and Apple Audio products. The ideal candidate thrives in ambiguity, is exceptionally organized, relentlessly detail-oriented, and an exceptional communicator at all levels of the organization. Preferred Qualifications Proven experience in GenAI application building with agents and agentic workflows. Experience with LLM and LMM development and fine-tuning. Experience applying ML techniques in manufacturing, testing, or hardware optimization. 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. Hands-on experience with LangChain and LlamaIndex, enabling RAG applications and LLM orchestration. Ability to meaningfully present results of analyses in a clear and impactful manner, breaking down complex ML/LLM concepts for non-technical audiences. Proven experience in leading and mentoring teams. Minimum Qualifications 3+ 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. Ability to travel internationally - up to 10% 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 . 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 $181,100 and $272,100, 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.

Hard Skills 7
Skill Source Confidence
Docker llm_hard
100%
Kubernetes llm_hard
100%
Large Language Models (LLMs) llm_hard
100%
Distributed Computing llm_hard
100%
Fine-tuning Models llm_hard
100%
RAG (Retrieval-Augmented Generation) llm_hard
100%
Model Deployment llm_hard
80%
Soft Skills 7
Skill Source Confidence
Explaining Complex Ideas Clearly llm_soft
100%
Presentation Skills llm_soft
100%
Cross-Functional Communication llm_soft
100%
Mentoring llm_soft
100%
Leadership llm_soft
100%
Team Leadership llm_soft
100%
Written Communication llm_soft
80%
Apply Options
Publisher Direct Link
Indeed No Apply
ZipRecruiter Yes Apply
Teal No Apply
Glassdoor No Apply
SWE Career Center No Apply
MedTech Innovator Job Board No Apply
Nexxt No Apply
SonicJobs Yes Apply
API Logs for this Job
Query Country Status Response ms Created
Machine Learning Engineer - LLM extracted 4592 2026-03-28 10:56
Machine Learning Engineer - LLM classified 414 2026-03-28 10:24
machine learning engineer gb processed 16939 2026-03-28 10:08
Raw JSON
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