ML Engineer Jobs at Apple with Visa Sponsorship
ML Engineer jobs at Apple sit at the intersection of hardware and intelligence, spanning on-device inference, Core ML, and large-scale training infrastructure. Apple sponsors across multiple visa categories for this function, making it a realistic target if you're an international candidate with a strong machine learning background.
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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+ ML Engineer Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new ML Engineer Jobs at Apple.
Get Access To All JobsTips for Finding ML Engineer Jobs at Apple
Align your portfolio to Apple's ML stack
Apple prioritizes on-device ML, neural engine optimization, and privacy-preserving inference. Before applying, reframe your project work around model compression, Core ML deployment, or federated learning rather than cloud-scale training pipelines.
Target teams filing Labor Condition Applications early
Apple's LCA filings with DOL reveal which teams are actively hiring internationally. Search OFLC disclosure data by employer and job title to identify which ML specializations Apple is sponsoring right now, then target those specific roles.
Distinguish your visa pathway before the offer stage
Apple sponsors H-1B, E-3, TN, and H-1B1 visa, each with different timelines and filing windows. Know which category applies to your citizenship before you receive an offer so you can negotiate a realistic start date with the recruiting team.
Front-load your USCIS petition documentation
For ML Engineer roles, Apple's immigration team will need evidence that the position requires a degree in a specific field. Gather transcripts, your degree certificate, and any credential evaluations before your offer letter arrives to avoid delays in the I-129 filing.
Use Migrate Mate to filter Apple ML Engineer openings by visa type
Sponsored ML Engineer roles at Apple don't always surface easily on general job boards. Use Migrate Mate to filter Apple's open positions by the visa category that matches your status, saving you from applying to roles where sponsorship isn't available.
Flag OPT STEM extension eligibility during the offer negotiation
If you're on F-1 OPT, Apple's size and E-Verify enrollment make it a qualifying employer for the 24-month STEM extension. Confirming this during the offer stage gives you up to three years of runway before your H-1B lottery selection becomes urgent.
Frequently Asked Questions
Does Apple sponsor H-1B visas for ML Engineers?
Yes, Apple sponsors H-1B visas for ML Engineers and has a well-established immigration program to support international hires in this function. Apple participates in the annual H-1B lottery each April for cap-subject candidates. If you're already in H-1B visa status with another employer, Apple can file an H-1B transfer, letting you start work as soon as USCIS receives the petition.
How do I apply for ML Engineer jobs at Apple?
Apply directly through Apple's careers site, targeting ML Engineer roles by team, such as Core ML, Siri, or Silicon Engineering. Tailor your resume to Apple's on-device and privacy-focused ML priorities rather than general deep learning experience. Migrate Mate lists Apple's open ML Engineer positions filtered by visa sponsorship type, which makes it easier to find roles aligned with your specific status before applying.
Which visa types does Apple commonly use for ML Engineers?
Apple sponsors H-1B for most international ML Engineers and also files for H-1B1 visa (Chilean and Singaporean nationals), E-3 visa (Australian nationals), and TN visa (Canadian and Mexican nationals). Green Card sponsorship through EB-2 or EB-3 PERM is also available for longer-tenured employees. F-1 OPT and CPT are supported for students and recent graduates in qualifying programs.
What qualifications does Apple expect for ML Engineer roles?
Apple's ML Engineer postings consistently require a bachelor's degree or higher in Computer Science, Electrical Engineering, or a related field, which directly supports the H-1B specialty occupation standard. Beyond credentials, Apple looks for hands-on experience with model optimization for constrained hardware, proficiency in frameworks like PyTorch or JAX, and familiarity with low-latency inference requirements common in consumer device contexts.
How do I think about the timeline from offer to start date as an international ML Engineer candidate at Apple?
Timeline depends heavily on your visa category. E-3 and TN candidates can often start within four to six weeks of an offer if the Labor Condition Application is filed promptly with DOL. H-1B candidates without existing status must wait for an approved lottery selection, which runs on a federal fiscal year cycle starting October 1. Premium processing with USCIS is available and reduces H-1B adjudication to 15 business days once filed.