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 JobsDo you believe generative models can transform creative workflows and smart assistants used by billions? Do you believe it can fundamentally shift how people interact with devices and communicate, personalizing and tailoring experiences to their unique needs? SIML’s Content Understanding teams strives to turn cutting edge research into compelling user experiences that realize all these goals and more, working on Apple Intelligence technologies such as Image Playground, Genmoji, Generative Memories, Semantic Search, and many more.
You will be working alongside teams that are in charge of operating system wide embeddings, personalized RAG workstreams, tool calling, context compaction / efficiency & memory systems. Projects are focused on advancing Apple Intelligence capabilities, while working closely across disciplines with our partners in hardware engineering, design and product.
Description
We are looking for a senior technical leader experienced in architecting and deploying production scale multimodal ML. An ideal candidate has the ability to lead diverse cross functional efforts ranging from ML modeling, prototyping, validation and private learning. Solid ML fundamentals and an ability to place research contributions with respect to state of the art would be an essential part of the role. Experience with training and adapting large language models would be an important need.
This role includes the opportunity to partner with world class system engineers to prototype and incorporate bleeding edge algorithmic innovations in the context of emerging agentic experiences. Ability to interface with large scale modeling & data infrastructure is a huge plus.
Minimum Qualifications
PhD, or MSc in Computer Science/Electrical Engineering, or a related field (mathematics, physics or computer engineering); with a focus on machine learning, or comparable professional experience.
Hands on experience training LLMs/adapting pre-trained LLMs for downstream tasks & alignment.
Modeling experience at the intersection of NLP and Vision.
Proficiency in ML toolkit of choice, e.g., PyTorch.
Strong programming skills in Python.
Proven track record of research contributions demonstrated through publications in top-tier conferences, or open source contributions to algorithm.
Preferred Qualifications
Experience with building & deploying Multimodal-LLMs.
Familiarity with distributed training and large-scale data infrastructure.
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.
Do you believe generative models can transform creative workflows and smart assistants used by billions? Do you believe it can fundamentally shift how people interact with devices and communicate, personalizing and tailoring experiences to their unique needs? SIML’s Content Understanding teams strives to turn cutting edge research into compelling user experiences that realize all these goals and more, working on Apple Intelligence technologies such as Image Playground, Genmoji, Generative Memories, Semantic Search, and many more.
You will be working alongside teams that are in charge of operating system wide embeddings, personalized RAG workstreams, tool calling, context compaction / efficiency & memory systems. Projects are focused on advancing Apple Intelligence capabilities, while working closely across disciplines with our partners in hardware engineering, design and product.
Description
We are looking for a senior technical leader experienced in architecting and deploying production scale multimodal ML. An ideal candidate has the ability to lead diverse cross functional efforts ranging from ML modeling, prototyping, validation and private learning. Solid ML fundamentals and an ability to place research contributions with respect to state of the art would be an essential part of the role. Experience with training and adapting large language models would be an important need.
This role includes the opportunity to partner with world class system engineers to prototype and incorporate bleeding edge algorithmic innovations in the context of emerging agentic experiences. Ability to interface with large scale modeling & data infrastructure is a huge plus.
Minimum Qualifications
PhD, or MSc in Computer Science/Electrical Engineering, or a related field (mathematics, physics or computer engineering); with a focus on machine learning, or comparable professional experience.
Hands on experience training LLMs/adapting pre-trained LLMs for downstream tasks & alignment.
Modeling experience at the intersection of NLP and Vision.
Proficiency in ML toolkit of choice, e.g., PyTorch.
Strong programming skills in Python.
Proven track record of research contributions demonstrated through publications in top-tier conferences, or open source contributions to algorithm.
Preferred Qualifications
Experience with building & deploying Multimodal-LLMs.
Familiarity with distributed training and large-scale data infrastructure.
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 281+ 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.