Machine Learning Research Jobs at Apple with Visa Sponsorship
Machine Learning Research jobs at Apple involve working on foundational AI problems across devices, services, and silicon, with the company maintaining a consistent track record of sponsoring international researchers across multiple visa categories. If you're targeting these roles, Apple treats visa sponsorship as a standard part of hiring for qualified candidates.
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Get Access To All JobsImagine 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. Dynamic, smart people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same passion for innovation that goes into our products also applies to our practices, strengthening our commitment to leave the world better than we found it. Join us to help deliver the next groundbreaking Apple product.
Do you love working on challenges that no one has solved yet? As a member of our dynamic group, you will have the unique and rewarding opportunity to craft upcoming products that will delight and inspire millions of Apple's customers every single day.
Description
Apple's ML Data Operations group is seeking a Data Operations Engineer to support internal data collection efforts powering our next generation of consumer machine learning features. In this role, you will work shoulder-to-shoulder with full-time Apple scientists and engineers, not just coordinating logistics, but developing a genuine technical understanding of the ML experiments you support. You will be responsible for the hands-on bring-up, execution, and quality oversight of internal data collection studies, operating in a highly collaborative and technically demanding cross-functional environment.
Responsibilities:
- Plan, execute, and track internal ML data collection studies in close collaboration with researchers, engineers, and scientists across the organization
- Develop a working understanding of the ML experiments being supported, including model objectives, data requirements, labeling, and evaluation criteria, to ensure datasets quality
- Bring up and maintain pre-release hardware and software platforms used for data collection, performing hands-on troubleshooting and triage to minimize study disruptions
- Create and maintain clear technical documentation for hardware/software platform setup, study protocols, and data handling procedures
- Manage day-to-day logistics of internal study sessions, including scheduling participants, configuring hardware and software setups, and maintaining smooth session flow
- Collaborate with algorithm, infrastructure, and hardware/software teams to gather and validate data collection requirements before and during study execution
- Track and communicate study progress, blockers, participant throughput, and dataset status to cross-functional partners and senior stakeholders
- Identify gaps in existing workflows and take initiative to define, document, and socialize process improvements
Minimum Qualifications
- Bachelor’s degree in HCI, Cognitive Science, Psychology, Engineering, Operations, or equivalent combination of education and relevant experience
- Experience supporting or executing human user studies, behavioral research, or data collection operations in an academic or industry setting
- Track record of partnering with ML engineers or researchers to define data requirements, quality standards, or collection specifications
Preferred Qualifications
- 10 years of experience in user research operations, data collection coordination, or a related technical operations role
- Hands-on familiarity with ML data pipelines, annotation tools, or dataset management practices
- Experience working directly with engineering and science teams, with comfort reading technical documentation, data schemas, or experiment specifications
- Familiarity with handling sensitive human data and adhering to strict privacy and consent protocols
- Highly organized self-starter who can manage multiple concurrent internal studies with minimal oversight
- Strong interpersonal and written communication skills, with the ability to collaborate fluidly across both technical and non-technical stakeholders
- Strong attention to detail with the ability to identify data anomalies and inconsistencies during live collection
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 $184,700 and $324,800, 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.
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. Dynamic, smart people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same passion for innovation that goes into our products also applies to our practices, strengthening our commitment to leave the world better than we found it. Join us to help deliver the next groundbreaking Apple product.
Do you love working on challenges that no one has solved yet? As a member of our dynamic group, you will have the unique and rewarding opportunity to craft upcoming products that will delight and inspire millions of Apple's customers every single day.
Description
Apple's ML Data Operations group is seeking a Data Operations Engineer to support internal data collection efforts powering our next generation of consumer machine learning features. In this role, you will work shoulder-to-shoulder with full-time Apple scientists and engineers, not just coordinating logistics, but developing a genuine technical understanding of the ML experiments you support. You will be responsible for the hands-on bring-up, execution, and quality oversight of internal data collection studies, operating in a highly collaborative and technically demanding cross-functional environment.
Responsibilities:
- Plan, execute, and track internal ML data collection studies in close collaboration with researchers, engineers, and scientists across the organization
- Develop a working understanding of the ML experiments being supported, including model objectives, data requirements, labeling, and evaluation criteria, to ensure datasets quality
- Bring up and maintain pre-release hardware and software platforms used for data collection, performing hands-on troubleshooting and triage to minimize study disruptions
- Create and maintain clear technical documentation for hardware/software platform setup, study protocols, and data handling procedures
- Manage day-to-day logistics of internal study sessions, including scheduling participants, configuring hardware and software setups, and maintaining smooth session flow
- Collaborate with algorithm, infrastructure, and hardware/software teams to gather and validate data collection requirements before and during study execution
- Track and communicate study progress, blockers, participant throughput, and dataset status to cross-functional partners and senior stakeholders
- Identify gaps in existing workflows and take initiative to define, document, and socialize process improvements
Minimum Qualifications
- Bachelor’s degree in HCI, Cognitive Science, Psychology, Engineering, Operations, or equivalent combination of education and relevant experience
- Experience supporting or executing human user studies, behavioral research, or data collection operations in an academic or industry setting
- Track record of partnering with ML engineers or researchers to define data requirements, quality standards, or collection specifications
Preferred Qualifications
- 10 years of experience in user research operations, data collection coordination, or a related technical operations role
- Hands-on familiarity with ML data pipelines, annotation tools, or dataset management practices
- Experience working directly with engineering and science teams, with comfort reading technical documentation, data schemas, or experiment specifications
- Familiarity with handling sensitive human data and adhering to strict privacy and consent protocols
- Highly organized self-starter who can manage multiple concurrent internal studies with minimal oversight
- Strong interpersonal and written communication skills, with the ability to collaborate fluidly across both technical and non-technical stakeholders
- Strong attention to detail with the ability to identify data anomalies and inconsistencies during live collection
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 $184,700 and $324,800, 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.
See all 287+ Machine Learning Research Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Research Jobs at Apple.
Get Access To All JobsTips for Finding Machine Learning Research Jobs at Apple
Align your research portfolio to Apple's focus areas
Apple's ML research priorities include on-device inference, neural network compression, and privacy-preserving machine learning. Tailor your publications, GitHub projects, or thesis work to these areas before applying, so your credentials map directly to what their research teams are evaluating.
Distinguish yourself with published or applied research
Apple recruits ML researchers through academic pipelines at venues like NeurIPS, ICML, and CVPR. Having peer-reviewed work or a strong preprint record signals readiness for a research-track role and strengthens the specialty occupation case USCIS needs to approve your H-1B petition.
Clarify your visa category before the offer stage
Apple sponsors H-1B, E-3 visa, TN, and F-1 OPT depending on your nationality and status. Ask your recruiter early which category applies to you so there are no surprises when the offer letter arrives and timelines for filing or transferring become critical.
Use Migrate Mate to find open Machine Learning Research roles at Apple
Apple's ML research openings are spread across product lines and aren't always easy to track. Use Migrate Mate to filter for sponsorship-confirmed roles at Apple so you're applying to positions where international hiring is already part of the process.
Understand how OPT cap-gap protects you during H-1B transitions
If you're on F-1 OPT when Apple files your H-1B, the cap-gap provision extends your work authorization through September 30 if your OPT expires during the waiting period. USCIS requires the petition to be filed before your OPT end date to qualify.
Prepare your DOL Labor Condition Application documentation early
Apple's legal team files the LCA with DOL before submitting your H-1B petition. Providing your exact job duties, worksite location, and start date accurately from day one avoids amendments later, which can delay your authorization by weeks.
Frequently Asked Questions
Does Apple sponsor H-1B visas for Machine Learning Researchs?
Yes, Apple sponsors H-1B visas for Machine Learning Research roles. These positions typically qualify as specialty occupations under USCIS standards because they require at minimum a bachelor's degree in computer science, machine learning, or a closely related technical field. Apple's legal team handles the LCA filing with DOL and the subsequent H-1B petition, which is standard practice for research-track hires.
Which visa types does Apple commonly use for Machine Learning Research roles?
Apple sponsors several visa categories for Machine Learning Research positions depending on your citizenship and current status. H-1B is the most common path for non-Australians and non-Canadians. Australian citizens are eligible for the E-3 visa, which carries no lottery and has a much faster processing timeline. Canadian and Mexican nationals may qualify for TN visa status. F-1 students can start on OPT before transitioning to a sponsored visa category.
What qualifications does Apple expect for Machine Learning Research roles?
Apple's Machine Learning Research positions typically require a PhD or master's degree in machine learning, computer science, statistics, or a related quantitative field. Practical experience with PyTorch or JAX, published research at top-tier venues like NeurIPS or CVPR, and familiarity with on-device or privacy-preserving ML methods are common differentiators. Industry research experience or strong open-source contributions can supplement an academic background.
How do I apply for Machine Learning Research jobs at Apple?
You can find Machine Learning Research roles on Apple's careers site, but filtering specifically for sponsorship-confirmed openings is easier through Migrate Mate, which curates Apple's listings by visa category. Once you apply, expect a multi-stage process including a technical screen, coding and system design rounds, and a research presentation. Timelines from application to offer can range from six to twelve weeks depending on team and role level.
How do I time my application if I'm on OPT or between visa statuses?
If you're on F-1 OPT, Apple can file your H-1B petition during the annual cap season starting in March for an October 1 start. If your OPT expires before October 1 and your petition is selected in the lottery, the cap-gap provision covers you through September 30. Starting your job search at least six to nine months before your OPT expires gives you enough runway to go through Apple's full interview process before the filing window opens.