AI ML Engineering Jobs at Apple with Visa Sponsorship
AI ML Engineering jobs at Apple involve building some of the company's most ambitious AI and machine learning work into its hardware and software ecosystem, with teams spanning roles from research scientists to production ML engineers. Apple has a consistent track record of sponsoring work visas for qualified AI ML Engineering candidates across multiple visa categories.
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Get Access To All JobsINTRODUCTION
We are looking for a Senior ML Researcher who is passionate about foundation model post-training, including Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL), and has experience with core capabilities such as instruction following, tool use, deep thinking, and reasoning. In this role, you will research, design, and deliver models where machine learning research meets real-world product impact.
You will work closely with research scientists, engineers, and product teams to find new ways that generative AI can help our creative users. Your mission is to improve the workflows of millions of creators by combining generative AI with Apple's human-centered design principles.
DESCRIPTION
What makes our work unique is we have many research opportunities in real-world use cases in multimodal space. Our goal is to develop targeted, task-specific capabilities within our models across a broad range of areas, including video understanding, reasoning, instruction following, and agentic tasks.
The role involves contributing to every stage of the post-training process:
- Formulate hypotheses for a use case
- Define data collection and annotation
- Build evaluations of model capabilities
- Apply SFT, advanced reward modeling, RL techniques, and distillation to develop and improve the post-training recipe
- Execute experiments, validate results, and communicate findings to the broader team
If you're passionate about doing research that ships in Apple's legendary products, this is the team for you.
MINIMUM QUALIFICATIONS
- MS in Computer Science, Machine Learning, or a related field, or equivalent practical experience
- Minimum 4+ years of research experience in Multi-Modal LLM training and evaluation
- Proven track record in multimodal SFT plus at least one of distillation, preference optimization, or online RL, backed by shipped models or rigorous experiments
- Strong programming skills in Python and at least one deep learning framework, such as JAX or PyTorch
- Ability to build intuition from a problem statement and translate it into dataset requirements, neural network design, and loss functions
PREFERRED QUALIFICATIONS
- PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience
- Experience in GRPO, DPO, Vision-OPD, and visual-token compression
- Publications in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV)
- Bonus: Experience in quantization, on-device models and SLM (Small Language Model)
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 $175,000 and $308,500, 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.
INTRODUCTION
We are looking for a Senior ML Researcher who is passionate about foundation model post-training, including Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL), and has experience with core capabilities such as instruction following, tool use, deep thinking, and reasoning. In this role, you will research, design, and deliver models where machine learning research meets real-world product impact.
You will work closely with research scientists, engineers, and product teams to find new ways that generative AI can help our creative users. Your mission is to improve the workflows of millions of creators by combining generative AI with Apple's human-centered design principles.
DESCRIPTION
What makes our work unique is we have many research opportunities in real-world use cases in multimodal space. Our goal is to develop targeted, task-specific capabilities within our models across a broad range of areas, including video understanding, reasoning, instruction following, and agentic tasks.
The role involves contributing to every stage of the post-training process:
- Formulate hypotheses for a use case
- Define data collection and annotation
- Build evaluations of model capabilities
- Apply SFT, advanced reward modeling, RL techniques, and distillation to develop and improve the post-training recipe
- Execute experiments, validate results, and communicate findings to the broader team
If you're passionate about doing research that ships in Apple's legendary products, this is the team for you.
MINIMUM QUALIFICATIONS
- MS in Computer Science, Machine Learning, or a related field, or equivalent practical experience
- Minimum 4+ years of research experience in Multi-Modal LLM training and evaluation
- Proven track record in multimodal SFT plus at least one of distillation, preference optimization, or online RL, backed by shipped models or rigorous experiments
- Strong programming skills in Python and at least one deep learning framework, such as JAX or PyTorch
- Ability to build intuition from a problem statement and translate it into dataset requirements, neural network design, and loss functions
PREFERRED QUALIFICATIONS
- PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience
- Experience in GRPO, DPO, Vision-OPD, and visual-token compression
- Publications in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV)
- Bonus: Experience in quantization, on-device models and SLM (Small Language Model)
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 $175,000 and $308,500, 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 AI ML Engineering Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI ML Engineering Jobs at Apple.
Get Access To All JobsTips for Finding AI ML Engineering Jobs at Apple
Align your portfolio to Apple's on-device focus
Apple prioritizes ML work that runs efficiently on its own silicon, including Neural Engine optimization and Core ML integration. Demonstrating experience with model compression, quantization, or edge inference directly signals relevance to their engineering priorities.
Target teams building Apple Intelligence features
Apple's AI ML Engineering openings cluster around Siri, Photos, Health, and the Apple Intelligence platform. Reviewing recently shipped product features helps you identify which internal teams are actively hiring and tailor your application accordingly.
Clarify your visa category before the offer stage
Apple sponsors H-1B, E-3, TN, and F-1 OPT depending on your nationality and status. Confirm which category applies to you early in recruiter conversations so there's no ambiguity when the offer and legal team processes begin.
Prepare for Apple's multi-round technical interviews
Apple's ML interview loop typically includes coding, ML system design, and a domain-specific research discussion. Having published work, open-source contributions, or documented production ML systems strengthens your case at every round.
Understand OPT timing relative to Apple's hiring cycles
If you're on F-1 OPT, verify your authorization end date before accepting an offer. Apple's onboarding timelines can run six to eight weeks, and STEM OPT extension applications must be filed through your DSO before your initial OPT expires.
Use Migrate Mate to find active AI ML Engineering roles at Apple
Apple posts AI ML Engineering roles across multiple teams simultaneously, and openings move quickly. Use Migrate Mate to browse current positions filtered specifically for visa-sponsored roles so you're applying to openings where sponsorship is already confirmed.
Frequently Asked Questions
Does Apple sponsor H-1B visas for AI ML Engineers?
Yes, Apple sponsors H-1B visas for AI ML Engineering roles. Because the H-1B is subject to an annual lottery, Apple typically submits registrations in March for the following fiscal year. If you're already on H-1B with another employer, Apple can file an H-1B transfer, which lets you start without waiting for a new cap slot.
Which visa types does Apple commonly sponsor for AI ML Engineering positions?
Apple sponsors several visa categories for AI ML Engineering roles depending on your nationality and current status. Australian citizens can use the E-3 visa, Canadian and Mexican nationals can qualify under TN visa, and F-1 graduates can begin on OPT or STEM OPT extension. For longer-term sponsorship, Apple also supports EB-2 and EB-3 Green Card pathways for qualifying engineers.
What qualifications does Apple expect for AI ML Engineering roles?
Apple's AI ML Engineering roles typically require a bachelor's degree in computer science, electrical engineering, or a related field, with a master's or PhD preferred for research-adjacent positions. Hands-on experience with frameworks like PyTorch or JAX, familiarity with Apple's Core ML ecosystem, and demonstrated work on production ML systems at scale are commonly expected across levels.
How do I apply for AI ML Engineering jobs at Apple?
You can apply directly through Apple's careers site or find visa-sponsored openings through Migrate Mate, which filters specifically for roles where sponsorship is confirmed. Apple's process for ML roles typically involves a recruiter screen, a technical phone interview, and a multi-round onsite or virtual loop covering coding, ML system design, and a domain discussion. Response timelines after applying range from two to six weeks depending on the team.
How do I time my Apple job search around H-1B cap deadlines?
The H-1B registration window opens in early March each year, with USCIS selecting registrations by late March. To be included in that cycle, you need an offer and a registered employer before the window closes. Targeting Apple roles between October and February gives you the best chance of securing an offer in time for your employer to register you before the deadline.