Job Detail

Machine Learning Engineer- GenAI

Data Science and AI Full–time
ID: #19683
Posted: 2026-03-10
Salary

Description

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. 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. 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. 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 $147,400 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 9
Skill Source Confidence
Fine-tuning Models llm_hard
100%
RAG (Retrieval-Augmented Generation) llm_hard
100%
Large Language Models (LLMs) llm_hard
100%
Transformers llm_hard
100%
Docker llm_hard
80%
MLOps llm_hard
80%
Kubernetes llm_hard
80%
Distributed Computing llm_hard
80%
Model Deployment llm_hard
80%
Soft Skills 5
Skill Source Confidence
Presentation Skills llm_soft
100%
Cross-Functional Communication llm_soft
100%
Explaining Complex Ideas Clearly llm_soft
100%
Leadership llm_soft
80%
Mentoring llm_soft
80%
Apply Options
Publisher Direct Link
Indeed No Apply
Glassdoor No Apply
The Muse No Apply
SaluteMyJob No Apply
AnitaB.org Job Board No Apply
Talent.com No Apply
WhatJobs No Apply
JobMonkey Jobs No Apply
API Logs for this Job
Query Country Status Response ms Created
Machine Learning Engineer- GenAI extracted 7880 2026-03-28 10:57
Machine Learning Engineer- GenAI classified 442 2026-03-28 10:24
machine learning engineer gb processed 16939 2026-03-28 10:08
Raw JSON
{
  "job_id": "ttTo4qm1eisxpLgDAAAAAA==",
  "job_city": "Cupertino",
  "job_state": "California",
  "job_title": "Machine Learning Engineer- GenAI",
  "job_country": "US",
  "job_benefits": null,
  "job_latitude": 37.322997799999996,
  "job_location": "Cupertino, CA, United States",
  "job_onet_soc": "15111100",
  "apply_options": [
    {
      "is_direct": false,
      "publisher": "Indeed",
      "apply_link": "https://www.indeed.com/viewjob?jk=0c609596a1a83ea1&utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic"
    },
    {
      "is_direct": false,
      "publisher": "Glassdoor",
      "apply_link": "https://www.glassdoor.com/job-listing/llm-machine-learning-engineer-apple-JV_IC1147422_KO0,29_KE30,35.htm?jl=1010061167466&utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic"
    },
    {
      "is_direct": false,
      "publisher": "The Muse",
      "apply_link": "https://www.themuse.com/jobs/apple/machine-learning-engineer-genai?utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic"
    },
    {
      "is_direct": false,
      "publisher": "SaluteMyJob",
      "apply_link": "https://salutemyjob.com/jobs/machine-learning-engineer-genai-cupertino-california/2678544679-2/?utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic"
    },
    {
      "is_direct": false,
      "publisher": "AnitaB.org Job Board",
      "apply_link": "https://jobs.anitab.org/companies/apple/jobs/70939065-machine-learning-engineer-genai?utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic"
    },
    {
      "is_direct": false,
      "publisher": "Talent.com",
      "apply_link": "https://www.talent.com/view?id=611454851601932162&utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic"
    },
    {
      "is_direct": false,
      "publisher": "WhatJobs",
      "apply_link": "https://www.whatjobs.com/jobs/machine-learning-engineer-genai/monte-vista-california?id=2581216042&utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic"
    },
    {
      "is_direct": false,
      "publisher": "JobMonkey Jobs",
      "apply_link": "https://www.jobmonkeyjobs.com/career/27476840/Machine-Learning-Engineer-Genai-California-Cupertino-7413?utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic"
    }
  ],
  "employer_logo": "https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcQBpMZEyCin4RgucdyRjDpUGK1kaTTpbyYkQHbK&s=0",
  "employer_name": "Apple",
  "job_is_remote": false,
  "job_longitude": -122.03218229999999,
  "job_posted_at": "18 days ago",
  "job_publisher": "Indeed",
  "job_apply_link": "https://www.indeed.com/viewjob?jk=0c609596a1a83ea1&utm_campaign=google_jobs_apply&utm_source=google_jobs_apply&utm_medium=organic",
  "job_highlights": {
    "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 $147,400 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",
      "Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program"
    ],
    "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",
      "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",
      "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"
    ],
    "Responsibilities": [
      "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",
      "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"
    ]
  },
  "job_max_salary": null,
  "job_min_salary": null,
  "job_description": "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.\n\nThe 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.\n\nIt 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.\n\nDescription\n\nProduct 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!\n\nYou 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.\n\nPreferred Qualifications\n\nProven experience in GenAI application building with agents and agentic workflows. Experience with LLM and LMM development and fine-tuning is a major plus.\n\nProficiency in using cutting-edge GenAI tools, i.e. Claude Code, Roo Code, etc.\n\nFamiliarity 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.\n\nHands-on experience with LangChain and LlamaIndex, enabling RAG applications and LLM orchestration.\n\nDeep understanding of transformer-based architectures (e.g., BERT, GPT, LLaMA) and their optimization for low-latency inference.\n\nAbility to meaningfully present results of analyses in a clear and impactful manner, breaking down complex ML/LLM concepts for non-technical audiences.\n\nExperience applying ML techniques in manufacturing, testing, or hardware optimization is a major plus.\n\nProven experience in leading and mentoring teams is a plus.\n\nMinimum Qualifications\n\n3+ 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).\n\nMasters in Artificial intelligence, Machine Learning, Computer Science, Statistics, Operations Research, Physics, Mechanical Engineering, Electrical Engineering or related field.\n\nApple 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 .\n\nPay & Benefits\n\nAt 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 $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.\n\nApple 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.\n\nNote: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.",
  "job_google_link": "https://www.google.com/search?ibp=htl;jobs&q&htidocid=ttTo4qm1eisxpLgDAAAAAA%3D%3D&hl=en-GB&shem=epsd1&shndl=37&shmd=H4sIAAAAAAAA_xWMMQoCMRBFsd0jWE1jI-tGBAu1WhZZBK3EWrJxSCJxJmQibOkdPIB38yTG5sOD9371mVSbkzbOE8IRdSJPFvZkC2NaQI_UHuD7esOdB5AiGAdM0DPbgNOdyznKVimR0FjJOnvTGH4oJhx4VCWS_1zF6YQx6IzX1Xo5NpHsfNbGGBA8QfeMmLInrqFra7iQz3iDc7lD-QFgpioLogAAAA&shmds=v1_ATWGeePO9JjuMqX0HVwMvmq_1tmqFEKKRXofIDksK_Qt3Oon-A&source=sh/x/job/li/m1/1#fpstate=tldetail&htivrt=jobs&htiq&htidocid=ttTo4qm1eisxpLgDAAAAAA%3D%3D",
  "employer_website": "https://www.apple.com",
  "job_onet_job_zone": "5",
  "job_salary_period": "YEAR",
  "job_apply_is_direct": false,
  "job_employment_type": "Full–time",
  "job_employment_types": [
    "FULLTIME"
  ],
  "job_posted_at_timestamp": 1773100800,
  "job_posted_at_datetime_utc": "2026-03-10T00:00:00.000Z"
}