H-1B Visa Machine Learning Jobs
Machine Learning roles qualify as H-1B visa specialty occupations under the computer and mathematical occupations category, requiring at least a bachelor's degree in computer science, statistics, or a related field. Employers file an LCA with DOL before petitioning USCIS, certifying that your wage meets the prevailing level for your work location.
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INTRODUCTION
Apple Services Engineering (ASE) builds experiences that touch hundreds of millions of customers every day. From personalized recommendations to proactive intelligence and large-scale commerce systems, we are transforming how users discover, engage, and transact across the Apple ecosystem. The ASE AI/ML organization sits at the nexus of these systems—where deep applied research, advanced machine learning, and large language models converge to drive high-impact innovation at unprecedented scale.
DESCRIPTION
We are seeking a Senior Machine Learning Engineer with demonstrated expertise in Generative AI, LLM architectures, and advanced NLP systems. This role is ideal for a hands-on technical leader who has taken novel ideas from research inception to production deployment, and who thrives in environments where ambiguity, scale, and cutting-edge innovation intersect. Here, you won’t just push the boundaries of what’s possible today—you’ll define what’s next.
What Sets This Role Apart
This is not a narrow modeling position. You will influence and implement foundational intelligence capabilities across Apple Services—spanning language understanding, behavioral inference, discovery, and growth optimization—while operating with the autonomy and scope expected of senior technical leadership at Apple.
Responsibilities
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Architect, design, and deploy LLM-powered systems that unlock new capabilities for personalization, intelligent automation, and customer understanding across Apple’s services ecosystem.
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Lead research in areas such as large-scale representation learning, semantic modeling, topic induction, natural language understanding, and retrieval-augmented generation (RAG).
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Develop and evolve taxonomies, embeddings, and model architectures capable of disentangling complex user or content behaviors in high-dimensional, unstructured data.
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Drive LLM fine-tuning, evaluation, safety alignment, and optimization strategies to ensure performant, compliant, and frictionless user experiences.
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Explore and productize methods such as parameter-efficient adaptation, multi-agent orchestration, active learning, RLHF, and novel inference optimization techniques.
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Collaborate with engineering, product, and design organizations to translate ambiguous problem spaces into robust ML systems with measurable business and customer impact.
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Build prototypes and production-grade solutions that advance Apple’s ability to reason over text, behavioral signals, and domain-specific knowledge at scale.
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Contribute to Apple’s leadership in AI through patent filings, publications, and internal thought leadership.
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Mentor and elevate other researchers, fostering excellence in experimentation, code quality, communication, and scientific rigor.
MINIMUM QUALIFICATIONS
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Ph.D. in Computer Science, Machine Learning, NLP, Statistics, or a related field—or equivalent industry experience delivering production AI systems.
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At least 6 years of experience in an applied research or machine learning role.
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Expert knowledge of deep learning and modern NLP, including transformer architectures and foundation model adaptation.
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Experience with LLM model development, including fine-tuning, instruction tuning, and prompt engineering for domain-specific reasoning.
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Proficiency in Python and ML frameworks such as PyTorch or TensorFlow, with experience deploying models in production systems.
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Strong understanding of distributed data processing systems (e.g., Spark) and large-scale experimentation.
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Proven ability to communicate research outcomes, architectural decisions, and technical tradeoffs to technical and non-technical stakeholders.
PREFERRED QUALIFICATIONS
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Hands-on experience with retrieval-augmented generation (RAG) pipelines and vector-based semantic search systems.
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Representation learning and semantic embeddings for clustering, categorization, and content understanding.
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Model evaluation frameworks for language quality, relevance, hallucination, and safety.
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Inference optimization techniques (quantization, distillation, model compression).
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Understanding of reinforcement learning, policy alignment, or RLHF for improving interactive AI systems.
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Experience developing personalization, ranking, or optimization algorithms at scale.
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Proven experience in the architectural design and development of RL or multi-armed bandit experiment platforms.
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A record of publications in top-tier ML/AI venues or patent filings demonstrating novel research contributions.
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.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship in Machine Learning
Verify your degree field matches
USCIS requires a direct relationship between your degree and the ML role. A computer science or statistics degree maps cleanly, but a business degree rarely does. If your degree is adjacent, gather course transcripts showing machine learning or data science coursework before applying.
Check prevailing wages before negotiating
Use the OFLC Wage Search to look up the Level I through Level IV wage for your specific SOC code and work location. Your offer must meet at least Level I, but most ML roles are filed at Level II or III, which affects what employers can realistically sponsor.
Target employers with cap-exempt filing pathways
Universities, nonprofit research organizations, and government research entities can file H-1B petitions year-round without entering the lottery. ML research roles at these institutions let you start work before October 1, bypassing the April registration window entirely.
Find verified H-1B sponsors on Migrate Mate
Search Migrate Mate to identify employers with confirmed LCA filing history for machine learning and data science roles. You'll see which companies have actually sponsored H-1B workers in your target occupation, not just which ones claim to be open to sponsorship.
Clarify remote work before the LCA is filed
Your employer's LCA ties your prevailing wage to a specific worksite location. If you're working remotely from a different metro area than the employer's office, a separate LCA must be filed for that location. Resolve this before the petition is submitted, not after.
Request premium processing if your OPT end date is close
USCIS offers premium processing on Form I-129, which guarantees a decision within 15 business days. If your OPT authorization expires within three to four months of your start date, ask your employer to elect premium processing to avoid a gap in work authorization.
H-1B Visa Machine Learning: Frequently Asked Questions
Does a machine learning role qualify as a specialty occupation for H-1B purposes?
Yes. Machine learning positions fall under computer and mathematical occupations and consistently qualify as specialty occupations because they require theoretical and practical application of highly specialized knowledge in algorithms, statistical modeling, or neural network architecture. USCIS expects your degree to be in a directly related field such as computer science, applied mathematics, or statistics, not a general business or unrelated technical discipline.
Which employers actually sponsor H-1B visas for machine learning jobs?
Technology companies, financial services firms, healthcare analytics organizations, and defense contractors are the most active H-1B sponsors for ML roles. The most reliable way to identify verified sponsors is to search Migrate Mate, which surfaces employers based on confirmed DOL LCA filing history for machine learning and related data science occupations, rather than self-reported sponsorship willingness.
How does the H-1B lottery affect machine learning job seekers specifically?
The annual H-1B cap applies to most private-sector ML roles, with registration opening each March and USCIS conducting a random lottery if registrations exceed the 85,000 cap. If you're not selected, employment at a cap-exempt institution such as a university research lab or qualifying nonprofit is the primary alternative that bypasses the lottery entirely and allows an immediate petition filing.
Can my employer file my H-1B petition while I'm working on OPT STEM extension?
Yes, and this is the standard path for most F-1 graduates. Your employer registers you in the March lottery, and if selected, files Form I-129 before October 1. Your STEM OPT remains valid until your H-1B status takes effect, provided your employer is E-Verify enrolled, which is a mandatory condition for all STEM OPT extensions. Confirm E-Verify enrollment before accepting an offer.
What happens to my H-1B status if my machine learning role changes significantly?
A material change in job duties, title, or work location can require your employer to file an amended H-1B petition with USCIS before the change takes effect. Moving from an individual contributor ML role to a managerial position, or shifting from model development to data engineering, are the kinds of changes that typically trigger an amendment. Ask your employer to review any significant role change with their immigration counsel before it's finalized.