Machine Learning Jobs at Apple with Visa Sponsorship
Machine Learning jobs at Apple involve building the models powering Siri, on-device inference, computer vision, and neural engine optimization across its entire product ecosystem. Apple has a consistent track record of sponsoring work visas for ML engineers and researchers, covering multiple visa categories from OPT through permanent residence.
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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 285+ Machine Learning Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Jobs at Apple.
Get Access To All JobsTips for Finding Machine Learning Jobs at Apple
Tailor your ML portfolio to Apple's stack
Apple prioritizes on-device inference, Core ML, and privacy-preserving machine learning. Showcase projects involving model compression, neural architecture search, or federated learning rather than cloud-scale training work more relevant to other employers.
Target teams publishing Apple research
Apple's ML Research blog and publications on arXiv signal which teams are actively hiring. Applying to roles whose published work aligns with your specialization puts you in front of hiring managers with an existing research agenda that matches your background.
Clarify your OPT timeline before applying
STEM OPT extensions give F-1 graduates up to three years of work authorization. If your OPT expires mid-cycle, flag your timeline early in recruiter conversations so Apple's immigration team can sequence an H-1B cap filing or E-3 application accordingly.
Understand which visa fits your citizenship
Australian citizens can pursue the E-3 visa, which has no lottery and allows year-round filing, while Canadians may qualify for TN status. Knowing which category applies before your offer stage prevents delays when Apple's legal team initiates the petition.
Prepare for a multi-round technical process
Apple's ML interviews typically include coding screens, ML system design rounds, and a domain-specific research discussion. Having your GitHub, publications, and documented project outcomes ready before the recruiter screen shortens the credentialing review Apple's immigration team conducts post-offer.
Use Migrate Mate to find open ML roles at Apple
Apple posts Machine Learning roles across teams simultaneously, and openings move quickly. Search and filter active Apple ML positions by visa type and team focus on Migrate Mate to identify roles aligned with your specialization before they close.
Frequently Asked Questions
Does Apple sponsor H-1B visas for Machine Learning roles?
Yes, Apple sponsors H-1B visas for Machine Learning engineers and researchers. Apple participates in the annual H-1B cap lottery each April for candidates without existing H-1B status, and can also file for cap-exempt transfers if you already hold an approved H-1B petition from a previous employer. Apple's immigration team manages the full filing process after an offer is accepted.
How do I apply for Machine Learning jobs at Apple?
Applications go through Apple's careers portal at jobs.apple.com, where ML roles are listed by team, such as Siri, Core ML, or Health AI. You can also browse and filter open Apple Machine Learning positions by visa type on Migrate Mate, which surfaces roles actively open to sponsored candidates. Tailoring your resume to Apple's on-device ML focus improves your chances of passing initial screening.
Which visa types does Apple commonly use for Machine Learning roles?
Apple sponsors H-1B and H-1B1 visas for ML roles, along with E-3 visas for Australian citizens and TN visa status for Canadian and Mexican nationals. F-1 OPT and CPT are accepted for students and recent graduates, and Apple files EB-2 and EB-3 immigrant visa petitions, including PERM labor certifications, for employees pursuing permanent residence.
What qualifications does Apple expect for sponsored Machine Learning positions?
Most Apple ML roles require a Bachelor's degree at minimum in Computer Science, Electrical Engineering, or a related field, with many research and senior roles preferring a Master's or PhD. Hands-on experience with PyTorch or JAX, familiarity with model optimization for edge deployment, and a track record of shipping ML features in production environments are consistently emphasized across Apple job descriptions for this function.
How do I time my application around the H-1B cap and OPT expiration?
USCIS opens H-1B registrations in March each year, with cap-subject petitions taking effect October 1 if selected. If your OPT expires before October 1, Apple can file a cap-gap extension to bridge the gap as long as your H-1B petition is pending. Starting your job search no later than December or January gives enough runway to receive an offer, complete Apple's internal review, and register before the March window closes.