STEM OPT Machine Learning Research Jobs
Machine Learning Research roles at E-Verify-enrolled employers qualify for the 24-month STEM OPT extension, giving you up to 36 months of F-1 work authorization. Eligible degrees span computer science, statistics, electrical engineering, and related STEM CIP codes. Your employer must file a formal I-983 training plan with your DSO before your extension begins.
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Get Access To All JobsSUMMARY
The Gatos team is a cross-discipline production and research data annotation team within Video Engineering. We deliver the labeled data that algorithm teams use to build and evaluate features for millions of devices and users around the world. We're looking for an operations engineer who will own annotation projects from the first request to delivered data. That includes a growing set of AI-assisted and agent-based workflows, where models do much of the labeling and people guide, review and verify the results.
DESCRIPTION
In this role you will: Work with algorithm teams to define what success looks like for each data request, and translate it into a clear task specification, labeling guidelines and a quality bar. Own annotation projects end to end, from pilot through production to delivery, and be accountable for quality, schedule and the usefulness of the data to the customer. Design, implement, and run AI-assisted labeling workflows: models pre-label, automated steps handle routine work, and people focus on judgment and verification. Measure the impact on quality, throughput and cost. Set acceptance criteria, run quality checks and audits, analyze error patterns, and close the loop with guideline owners and labeling teams. Track project status and risks, and raise issues early with a clear ask and a root cause. Collaborate with data scientists, software and infrastructure engineers, data collection teams, business operations, and external labeling teams across time zones. Improve how the team works by building and sharing tools and workflows that use AI.
MINIMUM QUALIFICATIONS
- BS and a minimum of 3 years relevant industry experience.
- Experience delivering data for machine learning, such as data annotation, data operations, or technical program management.
- Experience defining annotation tasks, labeling guidelines, and quality metrics.
- Experience serving as the accountable owner for projects that span multiple teams, from ambiguous requirements to delivery.
- Experience working hands-on with data and technical tools, such as writing basic SQL queries or scripts, analyzing data in spreadsheets, or configuring labeling platforms.
PREFERRED QUALIFICATIONS
- Experience with model-assisted labeling, pseudo-labeling, or agent-based workflows, including judging where people must stay in the loop.
- Experience with Python or SQL for data analysis and automation.
- Familiarity with computer vision data such as images, video, depth, or 3D.
- Experience building reports or dashboards for cross-functional partners.
- Clear written and verbal communication, including status updates and escalations to senior leaders.
- Works effectively across time zones with internal teams and external partners.
- Defines success with customers before starting the work, and adapts as their needs change.
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
The Gatos team is a cross-discipline production and research data annotation team within Video Engineering. We deliver the labeled data that algorithm teams use to build and evaluate features for millions of devices and users around the world. We're looking for an operations engineer who will own annotation projects from the first request to delivered data. That includes a growing set of AI-assisted and agent-based workflows, where models do much of the labeling and people guide, review and verify the results.
DESCRIPTION
In this role you will: Work with algorithm teams to define what success looks like for each data request, and translate it into a clear task specification, labeling guidelines and a quality bar. Own annotation projects end to end, from pilot through production to delivery, and be accountable for quality, schedule and the usefulness of the data to the customer. Design, implement, and run AI-assisted labeling workflows: models pre-label, automated steps handle routine work, and people focus on judgment and verification. Measure the impact on quality, throughput and cost. Set acceptance criteria, run quality checks and audits, analyze error patterns, and close the loop with guideline owners and labeling teams. Track project status and risks, and raise issues early with a clear ask and a root cause. Collaborate with data scientists, software and infrastructure engineers, data collection teams, business operations, and external labeling teams across time zones. Improve how the team works by building and sharing tools and workflows that use AI.
MINIMUM QUALIFICATIONS
- BS and a minimum of 3 years relevant industry experience.
- Experience delivering data for machine learning, such as data annotation, data operations, or technical program management.
- Experience defining annotation tasks, labeling guidelines, and quality metrics.
- Experience serving as the accountable owner for projects that span multiple teams, from ambiguous requirements to delivery.
- Experience working hands-on with data and technical tools, such as writing basic SQL queries or scripts, analyzing data in spreadsheets, or configuring labeling platforms.
PREFERRED QUALIFICATIONS
- Experience with model-assisted labeling, pseudo-labeling, or agent-based workflows, including judging where people must stay in the loop.
- Experience with Python or SQL for data analysis and automation.
- Familiarity with computer vision data such as images, video, depth, or 3D.
- Experience building reports or dashboards for cross-functional partners.
- Clear written and verbal communication, including status updates and escalations to senior leaders.
- Works effectively across time zones with internal teams and external partners.
- Defines success with customers before starting the work, and adapts as their needs change.
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 424+ STEM OPT Machine Learning Research Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT Machine Learning Research Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization in Machine Learning Research
Verify your CIP code before applying
Check that your degree's Classification of Instructional Programs code appears on the USCIS STEM Designated Degree Program List. Computer science, statistics, and applied mathematics codes typically qualify, but interdisciplinary programs sometimes don't. Confirm with your DSO before targeting roles.
Search employers through Migrate Mate first
Filter your Machine Learning Research job search on Migrate Mate to surface employers with verified E-Verify enrollment. This cuts out the manual legwork of cross-checking each company before you apply and saves you from pursuing dead-end opportunities.
Confirm E-Verify enrollment before accepting any offer
Ask your hiring contact directly whether the employer is enrolled in E-Verify and request their E-Verify Company ID number. An employer that can't provide this cannot legally employ STEM OPT students, regardless of how willing they are to support your extension.
Draft your I-983 training plan before your start date
USCIS requires a completed I-983 on file with your DSO before your STEM OPT extension activates. For Machine Learning Research roles, map specific projects and deliverables to learning objectives that align with your STEM degree field. Generic plans get rejected.
Target research labs with existing OPT infrastructure
University-affiliated research centers, national labs, and large tech R&D divisions process STEM OPT extensions regularly and have HR staff familiar with the I-983 requirements. First-time STEM OPT employers often cause delays because they're unfamiliar with their obligations under the training plan.
Use O*NET to frame your role's specialty occupation credentials
Pull the Machine Learning Research occupation profile from O*NET and match your degree field to the listed knowledge and skills requirements. This documentation strengthens your case if your employer or DSO needs to justify how your degree directly relates to the role.
Frequently Asked Questions
Does a Machine Learning Research role qualify for the STEM OPT extension?
Yes, provided your degree falls under a STEM-designated CIP code and the role directly applies skills from that field. Machine Learning Research positions typically satisfy this because they require quantitative reasoning, algorithm development, and statistical modeling rooted in computer science, mathematics, or engineering disciplines. Confirm your specific degree's eligibility with your DSO using the USCIS STEM Designated Degree Program List.
What E-Verify obligation does my employer have for my STEM OPT?
Your employer must be actively enrolled in E-Verify at the time your STEM OPT extension begins. Enrollment alone isn't sufficient if it lapsed. You can ask your employer to show you their E-Verify Company ID or employer participation page. If they're not enrolled, they cannot legally employ you under a STEM OPT extension, and you'd need to find an enrolled employer before your initial OPT period ends.
What goes into the I-983 training plan for a research role?
The I-983 requires a description of the research objectives, the specific skills you'll develop, how those skills connect to your STEM degree, and measurable goals your employer will evaluate. For Machine Learning Research, this typically means documenting model development cycles, experimental design responsibilities, and technical mentorship structures. Both you and a company supervisor must sign it, and your DSO must receive it before your extension is approved.
How does cap-gap protection work if I'm in a Machine Learning Research role during H-1B season?
If your employer files an H-1B visa petition on your behalf before your OPT expires and you're selected in the lottery, cap-gap automatically extends your work authorization through September 30 of that year. You can continue working in your Machine Learning Research role without interruption during this period. USCIS issues no separate document for cap-gap, your I-20 noting the cap-gap extension serves as proof of authorized status.
Where can I find Machine Learning Research jobs at E-Verify employers?
Migrate Mate filters job listings specifically for employers enrolled in E-Verify, so you're not wasting applications on companies that can't support your STEM OPT extension. Machine Learning Research roles at qualifying employers span university research divisions, national laboratories, and technology companies with active R&D programs. Searching through Migrate Mate surfaces only employers who meet the E-Verify requirement before you apply.