ML Research Engineer Jobs at Apple with Visa Sponsorship
ML Research Engineer jobs at Apple sit at the intersection of fundamental research and product-scale deployment, covering areas like neural architecture, on-device inference, and silicon-aware model optimization. Apple has a consistent track record of sponsoring work visas for this function across multiple visa categories.
Find ML Research Engineer Jobs at AppleOverview
Showing 5 of 23+ ML Research Engineer Jobs at Apple
See all ML Research Engineer Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new ML Research Engineer Jobs at Apple.
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 ML Research Engineer Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new ML Research Engineer Jobs at Apple.
Get Access To All JobsTips for Finding ML Research Engineer Jobs at Apple
Align your research to Apple Silicon
Apple's ML hiring strongly favors candidates with experience optimizing models for constrained hardware environments. Frame your resume and publications around on-device inference, quantization, or neural engine efficiency to match what Apple's teams are actively building.
Target teams through published research
Apple's ML Research Engineers often publish through CVPR, NeurIPS, and ICML. Identify the specific Apple research group whose papers align with your work, then apply to roles tied to that team rather than casting broadly across all open positions.
Clarify your visa category before interviewing
Apple sponsors several visa types for this role. Know which category applies to your situation before your recruiter screen so you can ask targeted questions about their process for that specific visa, not just general sponsorship willingness.
Prepare for the H-1B cap timeline early
If your offer lands outside a cap-exempt pathway, H-1B registration opens in March with an October 1 start date. Coordinating your offer acceptance, I-129 filing, and start date around this window requires planning months before you'd actually begin work.
Document specialty occupation evidence thoroughly
USCIS scrutinizes ML roles when the job description uses broad language. Work with Apple's immigration counsel to ensure the LCA and I-129 petition specifically describe the theoretical and applied research duties that require an advanced degree in a relevant field.
Search verified sponsoring roles on Migrate Mate
Confirming which ML Research Engineer openings at Apple are actively tied to sponsorship saves time during a targeted job search. Migrate Mate filters roles by visa type so you reach out to the right positions from the start.
Frequently Asked Questions
Does Apple sponsor H-1B visas for ML Research Engineers?
Yes, Apple sponsors H-1B visas for ML Research Engineer roles. Apple files petitions through the standard USCIS cap process as well as through cap-exempt pathways where applicable. Because ML Research is a specialized function requiring advanced technical credentials, Apple's immigration team treats these roles as clear specialty occupation cases when preparing the petition documentation.
How do I apply for ML Research Engineer jobs at Apple?
Apply directly through Apple's careers portal, but increase your chances by targeting the specific research domain you work in rather than applying to every open role. Apple's ML Research teams are organized around areas like vision, speech, and on-device learning. Tailoring your application materials to the relevant team's published work signals genuine fit. You can browse currently open roles with confirmed sponsorship through Migrate Mate.
Which visa types does Apple commonly use for ML Research Engineers?
Apple sponsors H-1B, H-1B1 visa, E-3 visa, TN visa, and F-1 OPT and CPT for ML Research Engineer roles, as well as immigrant pathways including EB-2 and EB-3. The right category depends on your citizenship. Australian citizens typically pursue the E-3 visa, Canadians and Mexicans use TN visa, and nationals from most other countries enter through H-1B, subject to the annual lottery.
What qualifications does Apple expect for ML Research Engineer roles?
Apple's ML Research Engineer positions typically require a PhD or a master's degree with substantial research output in machine learning, computer vision, natural language processing, or a closely related discipline. Publications at venues like NeurIPS, ICML, CVPR, or ICLR carry significant weight. Applied experience with large-scale model training, framework-level optimization, or hardware-aware ML is often expected alongside academic credentials.
How do I think about the timeline from offer to work authorization at Apple?
Timeline depends on your visa category. E-3 and TN holders can often start within four to eight weeks of an offer if consular appointments are available. H-1B cap cases require your start date to align with the October 1 fiscal year, meaning an offer in spring may involve a six-month gap before your first day. F-1 OPT holders can start sooner if their OPT authorization is already active.