AI Data Engineer Jobs at Apple with Visa Sponsorship
Apple's AI Data Engineer roles sit at the intersection of machine learning infrastructure and large-scale data systems, supporting products used by hundreds of millions of people. Apple has an established sponsorship track record across multiple visa categories, making it a realistic target for international candidates with the right technical background.
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Get Access To All JobsImagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The G&A Solutions Engineering organization at Apple primarily focuses on creative ways to engineer business solutions to meet growing needs of Apple's Finance, iTunes, Sales, Retail, and Services organizations. At core, our portfolio comprises of engineered custom solutions to process high volume transactions from Apple Pay, iTunes, Ads, App Store, iPhone Activations to Sales from Retail, Online, and Resellers. These solutions are based on cutting edge enterprise technologies ranging from Distributed Systems, Microservices, Java, Spring/Boot, Oracle, MongoDB, AWS services to AI/ML, Generative AI, and Blockchain. Accurately processing such high volume transactions is our core strength.
Description
The iRecon Payments team is seeking a highly motivated Data Engineer with a strong background in Data Science to drive our Agentic AI initiatives. In this role, you will build robust data pipelines, extract features, and curate high-quality datasets to train custom LLMs. You will navigate complex financial ecosystems to modernize data flows, ensuring accurate reconciliation, invoicing, and payments. You will play a critical role in building GenAI-powered solutions that improve user productivity and operational efficiency.
Responsibilities
- Design and build scalable data pipelines to enable Agentic AI solutions and custom LLM training
- Perform advanced feature engineering and dataset curation to optimize model performance
- Build upstream/downstream integrations with MCP (Model Context Protocol), Knowledge Graphs, and Vector Databases to support context engineering and retrieval (RAG)
- Work with large-scale financial transaction data to ensure precision in reconciliation, disbursements, and receipts
- Partner with cross-functional teams to translate business requirements into technical AI solutions
Minimum Qualifications
- 2+ years of experience building machine learning solutions using supervised/unsupervised learning, classification, recommendation systems, and clustering algorithms
- In-depth knowledge of transformer architecture, LLMs, and Agentic AI concepts
- Hands-on experience fine-tuning Large Language Models (LLMs) using PEFT/LoRA for domain-specific tasks
- Proven experience building and extending RAG, MCP (Model Context Protocol), or multi-agent frameworks (e.g., LangChain, LlamaIndex, AutoGen)
- Bachelor's degree in Computer Science, AI, Machine Learning, or relevant work experience
Preferred Qualifications
- 3+ years of experience building production-grade AI/ML solutions in the FinTech domain
- Strong written and verbal communication skills with the ability to articulate complex technical concepts
- Demonstrated ability to modernize legacy data systems and adapt to new AI architectures
- Experience with "Human-in-the-loop" data workflows for financial operations
- Demonstrated ability to quickly learn and adapt to new technologies and tools
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The G&A Solutions Engineering organization at Apple primarily focuses on creative ways to engineer business solutions to meet growing needs of Apple's Finance, iTunes, Sales, Retail, and Services organizations. At core, our portfolio comprises of engineered custom solutions to process high volume transactions from Apple Pay, iTunes, Ads, App Store, iPhone Activations to Sales from Retail, Online, and Resellers. These solutions are based on cutting edge enterprise technologies ranging from Distributed Systems, Microservices, Java, Spring/Boot, Oracle, MongoDB, AWS services to AI/ML, Generative AI, and Blockchain. Accurately processing such high volume transactions is our core strength.
Description
The iRecon Payments team is seeking a highly motivated Data Engineer with a strong background in Data Science to drive our Agentic AI initiatives. In this role, you will build robust data pipelines, extract features, and curate high-quality datasets to train custom LLMs. You will navigate complex financial ecosystems to modernize data flows, ensuring accurate reconciliation, invoicing, and payments. You will play a critical role in building GenAI-powered solutions that improve user productivity and operational efficiency.
Responsibilities
- Design and build scalable data pipelines to enable Agentic AI solutions and custom LLM training
- Perform advanced feature engineering and dataset curation to optimize model performance
- Build upstream/downstream integrations with MCP (Model Context Protocol), Knowledge Graphs, and Vector Databases to support context engineering and retrieval (RAG)
- Work with large-scale financial transaction data to ensure precision in reconciliation, disbursements, and receipts
- Partner with cross-functional teams to translate business requirements into technical AI solutions
Minimum Qualifications
- 2+ years of experience building machine learning solutions using supervised/unsupervised learning, classification, recommendation systems, and clustering algorithms
- In-depth knowledge of transformer architecture, LLMs, and Agentic AI concepts
- Hands-on experience fine-tuning Large Language Models (LLMs) using PEFT/LoRA for domain-specific tasks
- Proven experience building and extending RAG, MCP (Model Context Protocol), or multi-agent frameworks (e.g., LangChain, LlamaIndex, AutoGen)
- Bachelor's degree in Computer Science, AI, Machine Learning, or relevant work experience
Preferred Qualifications
- 3+ years of experience building production-grade AI/ML solutions in the FinTech domain
- Strong written and verbal communication skills with the ability to articulate complex technical concepts
- Demonstrated ability to modernize legacy data systems and adapt to new AI architectures
- Experience with "Human-in-the-loop" data workflows for financial operations
- Demonstrated ability to quickly learn and adapt to new technologies and tools
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
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Get Access To All JobsTips for Finding AI Data Engineer Jobs at Apple Jobs
Align your portfolio to Apple's ML stack
Apple's AI Data Engineering work centers on on-device intelligence and privacy-preserving ML pipelines. Showcasing experience with distributed data infrastructure, CoreML-adjacent tooling, or federated learning signals direct relevance before your resume reaches a recruiter.
Target roles tied to Apple Intelligence
Apple's generative AI push has concentrated data engineering hiring around its Apple Intelligence initiative. Filtering by teams like Siri, Core ML, and Health AI increases your odds of landing a role with active headcount and sponsorship budget already approved.
Request premium processing during H-1B filing
USCIS premium processing delivers a decision within 15 business days. For AI Data Engineer roles with a hard start date tied to a product cycle, ask Apple's immigration team upfront whether they'll elect premium to avoid a months-long wait.
Use Migrate Mate to find open AI Data Engineer roles at Apple
Sponsorship-eligible positions aren't always labeled as such on general job boards. Search Migrate Mate to filter Apple's current AI Data Engineer openings by visa type so you're only applying to roles where sponsorship is already confirmed.
Prepare your credentials for specialty occupation review
USCIS scrutinizes whether an AI Data Engineer role qualifies as a specialty occupation under H-1B rules. Gather transcripts, degree equivalency evaluations if your credential is from outside the U.S., and any documentation linking your specific degree field to the role.
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Find AI Data Engineer at Apple JobsFrequently Asked Questions
Does Apple sponsor H-1B visas for AI Data Engineers?
Yes, Apple sponsors H-1B visas for AI Data Engineer roles. Because H-1B is subject to an annual lottery with an 85,000-slot cap, Apple typically files petitions in April for an October 1 start date. Candidates already in H-1B status transferring from another employer can often start sooner through cap-exempt portability provisions.
How do I apply for AI Data Engineer jobs at Apple?
Applications go through Apple's careers portal at jobs.apple.com. The process typically involves a recruiter screen, a technical phone interview focused on data modeling and ML pipeline design, and a virtual or on-site loop with cross-functional teams. Sponsorship discussions happen with the recruiter early in the process, so raise your visa situation before the offer stage to avoid delays.
Which visa types does Apple commonly use for AI Data Engineer roles?
Apple sponsors H-1B for most nationalities, E-3 exclusively for Australian citizens, TN for Canadian and Mexican nationals in qualifying technical occupations, and F-1 OPT and CPT for students finishing U.S. degrees. For permanent residence, Apple supports EB-2 and EB-3 green card pathways, which typically begin after you've established a track record in the role.
What qualifications does Apple expect for AI Data Engineer roles?
Most AI Data Engineer postings at Apple require a bachelor's degree in computer science, data engineering, or a closely related field, with a master's or PhD preferred for research-adjacent teams. Practical experience with large-scale data pipelines, ML feature stores, and privacy-focused data handling is weighted heavily. Apple's on-device AI focus means familiarity with edge inference constraints is a differentiator.
How do I find AI Data Engineer roles at Apple that offer visa sponsorship?
Not every job listing explicitly states which visa categories an employer will support, which makes filtering difficult on general platforms. Migrate Mate lets you browse AI Data Engineer openings at Apple filtered by the specific visa types Apple sponsors, so you can identify the right roles before investing time in an application.
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