STEM OPT Machine Learning Jobs
Machine Learning roles in data science, NLP, and computer vision fall under STEM-designated CIP codes, making them eligible for the 24-month STEM OPT extension beyond your initial 12 months. Your employer must be enrolled in E-Verify and sign an I-983 training plan before your DSO can authorize the extension.
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Wonder how Apple's Media Products show relevant search results and recommendations across Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Design, build, and deploy recommendation models that personalize the App Store for billions of users worldwide! See your work touch the lives of billions of Apple users worldwide. The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, Games and Apple Fitness+. And we do it on a massive scale, meeting Apple's high expectations with high performance, to deliver a huge variety of entertainment in over 35 languages to more than 150 countries. Our researchers and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple's unique integration of hardware, software, and services, designers, scientists and engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here.
DESCRIPTION
We are looking for an exceptional Machine Learning Engineer to help us design, build, and ship recommendation models that power personalization across the App Store. With your expertise, we want to develop novel solutions to power personalized experiences across the App Store that enrich the lives of our customers. You will have the incredible opportunity to partner with researchers to see cutting-edge AI models deployed reliably at Apple's truly incredible global scale.
MINIMUM QUALIFICATIONS
- Bachelor's and Master's in a quantitative field, including Computer Science, Mathematics, Statistics, Physics, etc.
- 3+ years of relevant work experience.
- Hands-on experience with production-level recommender systems.
- Deep knowledge of recommendation systems, design patterns and tools, with particular depth in deep-learning architectures and multi-task modeling.
- Proven track record of shipping recommendation models to production at scale, with a strong understanding of the constraints of serving billions of users.
- Knowledge of modern recommendation architectures across retrieval and ranking, multi-task learning, sequence and transformer-based models, generative recommenders, and multi-objective optimization.
- Proven grasp of the open-source Python ML/AI tech stack, including TensorFlow, PyTorch, scikit-learn, numpy-scipy-pandas.
- Familiarity with big data technologies and distributed computing (e.g., Spark, Hadoop, Kafka).
- Familiarity with using LLM-powered tools (coding and research assistants) to accelerate day-to-day engineering and research workflows.
- Strong written & oral communication skills.
PREFERRED QUALIFICATIONS
- PhD in a quantitative field, including Computer Science, Mathematics, Statistics, Physics, etc.
COMPENSATION
- Base pay range for this role is between $142,300 and $263,300, 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.
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.
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.
Apple accepts applications to this posting on an ongoing basis.
SUMMARY
Wonder how Apple's Media Products show relevant search results and recommendations across Apple's media offerings - including App Store, Apple TV, Apple Music, Apple Podcasts, and Apple Books? Come join us! Design, build, and deploy recommendation models that personalize the App Store for billions of users worldwide! See your work touch the lives of billions of Apple users worldwide. The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. We are the people who power the App Store, Apple TV, Apple Music, Apple Podcasts, Games and Apple Fitness+. And we do it on a massive scale, meeting Apple's high expectations with high performance, to deliver a huge variety of entertainment in over 35 languages to more than 150 countries. Our researchers and engineers build secure, end-to-end solutions powered by machine learning. Thanks to Apple's unique integration of hardware, software, and services, designers, scientists and engineers here partner to get behind a single unified vision. That vision always includes a deep commitment to strengthening Apple's privacy policy, one of Apple's core values. Although services are a bigger part of Apple's business than ever before, these teams remain small, flexible, and multi-functional, offering greater exposure to the array of opportunities here.
DESCRIPTION
We are looking for an exceptional Machine Learning Engineer to help us design, build, and ship recommendation models that power personalization across the App Store. With your expertise, we want to develop novel solutions to power personalized experiences across the App Store that enrich the lives of our customers. You will have the incredible opportunity to partner with researchers to see cutting-edge AI models deployed reliably at Apple's truly incredible global scale.
MINIMUM QUALIFICATIONS
- Bachelor's and Master's in a quantitative field, including Computer Science, Mathematics, Statistics, Physics, etc.
- 3+ years of relevant work experience.
- Hands-on experience with production-level recommender systems.
- Deep knowledge of recommendation systems, design patterns and tools, with particular depth in deep-learning architectures and multi-task modeling.
- Proven track record of shipping recommendation models to production at scale, with a strong understanding of the constraints of serving billions of users.
- Knowledge of modern recommendation architectures across retrieval and ranking, multi-task learning, sequence and transformer-based models, generative recommenders, and multi-objective optimization.
- Proven grasp of the open-source Python ML/AI tech stack, including TensorFlow, PyTorch, scikit-learn, numpy-scipy-pandas.
- Familiarity with big data technologies and distributed computing (e.g., Spark, Hadoop, Kafka).
- Familiarity with using LLM-powered tools (coding and research assistants) to accelerate day-to-day engineering and research workflows.
- Strong written & oral communication skills.
PREFERRED QUALIFICATIONS
- PhD in a quantitative field, including Computer Science, Mathematics, Statistics, Physics, etc.
COMPENSATION
- Base pay range for this role is between $142,300 and $263,300, 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.
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.
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.
Apple accepts applications to this posting on an ongoing basis.
See all 420+ STEM OPT Machine Learning Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT Machine Learning Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization in Machine Learning
Verify your degree's CIP code eligibility
Check that your degree program's CIP code appears on the STEM Designated Degree Program List published by USCIS. Computer Science (11.07), Electrical Engineering (14.10), and Statistics (27.05) all qualify, but not every data-adjacent program does.
Confirm E-Verify enrollment before applying
Machine Learning roles at startups and research labs often lack E-Verify enrollment, which disqualifies them from STEM OPT. Search the E-Verify employer search tool by company name before submitting any application.
Target employers with active ML-specific LCA filings
Use Migrate Mate to filter for employers with verified Labor Condition Application filings under SOC codes like 15-2051 (Data Scientists) and 15-1252 (Software Developers). These companies have already navigated STEM OPT and understand the I-983 obligation.
Negotiate your I-983 training plan before signing
Your offer letter is not enough: USCIS requires a signed I-983 detailing your ML learning objectives, supervision structure, and how the role relates to your degree. Raise this document with HR during the offer stage, not after your start date.
Check prevailing wage against the OFLC Wage Search
Your employer must pay at least the DOL prevailing wage for your occupation and location. Run your job title and county through the OFLC Wage Search to catch underpaid offers early, since a below-wage role can jeopardize future H-1B visa sponsorship.
Build a portfolio aligned with O*NET ML task definitions
O*NET defines Machine Learning Engineers and Data Scientists by specific tasks: model training, feature engineering, and deployment pipelines. Structure your GitHub portfolio and resume around those task definitions so your application maps cleanly to the specialty occupation standard.
Frequently Asked Questions
Which STEM degrees qualify for the STEM OPT extension in Machine Learning roles?
Degrees in Computer Science, Electrical Engineering, Statistics, Applied Mathematics, and Data Science typically qualify, provided their CIP code appears on the STEM Designated Degree Program List published by USCIS. A Machine Learning or AI-specific master's program qualifies if the CIP code is listed. Degrees in Business Analytics or Information Systems may not qualify, so confirm your CIP code with your DSO before targeting STEM OPT positions.
Does every Machine Learning employer need to be enrolled in E-Verify?
Yes, E-Verify enrollment is a hard requirement for STEM OPT. No employer exemptions exist regardless of company size, funding stage, or role seniority. Many early-stage AI startups and university spin-outs are not yet enrolled, so verify enrollment directly through the E-Verify employer search before accepting an offer. Migrate Mate filters for E-Verify-enrolled employers so you can focus on companies that are already eligible.
What goes into the I-983 training plan for a Machine Learning role?
The I-983 must describe your learning objectives in relation to your degree, identify your direct supervisor, outline how the ML work connects to your field of study, and include a schedule for self-evaluations every six months. For Machine Learning roles, training plans typically document objectives around model development, research methodologies, and software engineering practices. Your employer signs the form and your DSO endorses it before USCIS authorizes your EAD extension.
How does cap-gap protection apply if my employer files for H-1B during my STEM OPT period?
If your employer files a timely H-1B petition before your STEM OPT EAD expires and you are selected in the lottery, cap-gap automatically extends your work authorization through September 30 of that fiscal year. You can continue working as a Machine Learning engineer during this period without a new EAD. If your petition is not selected, your STEM OPT authorization continues until its original expiration date, assuming the petition was filed before that date.
How do I find Machine Learning jobs where employers already understand STEM OPT requirements?
Search Migrate Mate for Machine Learning roles filtered by E-Verify-enrolled employers with active LCA filing history under relevant SOC codes. Employers who have previously filed LCAs for data science or software engineering roles are more likely to have internal processes for onboarding STEM OPT students and completing the I-983 training plan without delays.