AI ML Engineer Jobs at Apple with Visa Sponsorship
AI ML Engineer jobs at Apple require engineers who can move from research to production at scale, working across hardware-software integration that's unique to the company. Apple has a strong track record of sponsoring international talent across multiple visa categories for this function.
Find AI ML Engineer Jobs at AppleOverview
Showing 5 of 285+ AI ML Engineer Jobs at Apple
See all 285+ AI ML Engineer Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI ML Engineer Jobs at Apple.
Get Access To All JobsINTRODUCTION
Imagine being at the forefront of an evolution where innovative AI meets the elegance of Apple silicon. The On-Device Machine Learning team transforms groundbreaking research into practical applications, enabling billions of Apple devices to run powerful AI models locally, privately, and efficiently. We stand at the unique intersection of research, software engineering, hardware engineering, and product development, making Apple the leading destination for machine learning innovation.
Our team builds the essential infrastructure that enables machine learning at scale on Apple devices. This involves onboarding innovative architectures to embedded systems, developing optimization toolkits for model compression and acceleration, building ML compilers and runtimes for efficient execution, and creating comprehensive benchmarking and debugging toolchains. This infrastructure forms the backbone of Apple’s machine learning workflows across Camera, Siri, Health, Vision, and other core experiences, contributing to the overall Apple Intelligence ecosystem. If you are passionate about the technical challenges of running sophisticated ML models across all devices, from resource-constrained devices to powerful clusters, and eager to directly impact how machine learning operates across the Apple ecosystem, this role presents a great opportunity to work on the next generation of intelligent experiences on Apple platforms.
Our group is seeking an ML Infrastructure Engineer, with a focus on model compilation. The role entails working closely with model authoring, runtime, and performance teams to ensure that models can bring to bear the full capabilities of the hardware.
DESCRIPTION
We’re building an end-to-end developer experience for machine learning development that employs Apple’s vertical integration. This allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling, and analysis. This role focuses on the core runtime for execution across a wide variety of devices and use cases.
We’re seeking a highly motivated software engineer who is creative, versatile, and passionate about machine learning, common compiler optimizations, and system software engineering in the fast-paced and dynamic field of machine learning. We have an MLIR-based compiler stack, and use it to target the neural engine, GPU, and CPU in order to harness the full capabilities of the system for ML workflows and execution.
Responsibilities
- Inspire changes in our MLIR-based compiler in order to target improved runtime performance by demonstrating the capabilities of the hardware.
- Propose upstream changes in MLIR to better support new features and workflows in the hardware that lead to more optimal execution performance across all types of devices and device clusters.
- Own core pieces of the compiler stack enabling heterogeneous compute across Apple devices. We target execution of ML models across the Apple ecosystem from resource-constrained devices like Apple Watch, to the high-end Macs with Ultra SoCs.
- Work closely with hardware, software, and performance teams across the company to accelerate and optimize execution by taking advantage of the latest features in the hardware, OS, and drivers.
MINIMUM QUALIFICATIONS
- 3-5 years working on MLIR-based compilers.
- Familiarity with common ML model architectures, execution schemes, and operations.
- Familiarity with C++
- Familiarity with PyTorch or related training frameworks
PREFERRED QUALIFICATIONS
- Familiarity with Swift.
- Familiarity with programming paradigms for the GPU, CPU, and Neural Engine.
- Familiarity with writing kernels for ML model execution.
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.
INTRODUCTION
Imagine being at the forefront of an evolution where innovative AI meets the elegance of Apple silicon. The On-Device Machine Learning team transforms groundbreaking research into practical applications, enabling billions of Apple devices to run powerful AI models locally, privately, and efficiently. We stand at the unique intersection of research, software engineering, hardware engineering, and product development, making Apple the leading destination for machine learning innovation.
Our team builds the essential infrastructure that enables machine learning at scale on Apple devices. This involves onboarding innovative architectures to embedded systems, developing optimization toolkits for model compression and acceleration, building ML compilers and runtimes for efficient execution, and creating comprehensive benchmarking and debugging toolchains. This infrastructure forms the backbone of Apple’s machine learning workflows across Camera, Siri, Health, Vision, and other core experiences, contributing to the overall Apple Intelligence ecosystem. If you are passionate about the technical challenges of running sophisticated ML models across all devices, from resource-constrained devices to powerful clusters, and eager to directly impact how machine learning operates across the Apple ecosystem, this role presents a great opportunity to work on the next generation of intelligent experiences on Apple platforms.
Our group is seeking an ML Infrastructure Engineer, with a focus on model compilation. The role entails working closely with model authoring, runtime, and performance teams to ensure that models can bring to bear the full capabilities of the hardware.
DESCRIPTION
We’re building an end-to-end developer experience for machine learning development that employs Apple’s vertical integration. This allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling, and analysis. This role focuses on the core runtime for execution across a wide variety of devices and use cases.
We’re seeking a highly motivated software engineer who is creative, versatile, and passionate about machine learning, common compiler optimizations, and system software engineering in the fast-paced and dynamic field of machine learning. We have an MLIR-based compiler stack, and use it to target the neural engine, GPU, and CPU in order to harness the full capabilities of the system for ML workflows and execution.
Responsibilities
- Inspire changes in our MLIR-based compiler in order to target improved runtime performance by demonstrating the capabilities of the hardware.
- Propose upstream changes in MLIR to better support new features and workflows in the hardware that lead to more optimal execution performance across all types of devices and device clusters.
- Own core pieces of the compiler stack enabling heterogeneous compute across Apple devices. We target execution of ML models across the Apple ecosystem from resource-constrained devices like Apple Watch, to the high-end Macs with Ultra SoCs.
- Work closely with hardware, software, and performance teams across the company to accelerate and optimize execution by taking advantage of the latest features in the hardware, OS, and drivers.
MINIMUM QUALIFICATIONS
- 3-5 years working on MLIR-based compilers.
- Familiarity with common ML model architectures, execution schemes, and operations.
- Familiarity with C++
- Familiarity with PyTorch or related training frameworks
PREFERRED QUALIFICATIONS
- Familiarity with Swift.
- Familiarity with programming paradigms for the GPU, CPU, and Neural Engine.
- Familiarity with writing kernels for ML model execution.
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+ AI ML Engineer Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI ML Engineer Jobs at Apple.
Get Access To All JobsTips for Finding AI ML Engineer Jobs at Apple
Align your portfolio to Apple's on-device focus
Apple's AI ML roles emphasize privacy-preserving, on-device inference over cloud-heavy architectures. Showcase projects involving model compression, CoreML, or edge deployment to signal direct relevance before your application reaches a recruiter.
Target teams hiring under multiple visa categories
Apple sponsors H-1B, E-3, TN, and H-1B1 visas for AI ML Engineers. If you hold Australian citizenship, the E-3 sidesteps the H-1B lottery entirely and can be filed at any point in the year.
Prepare your degree equivalency documentation early
Apple's specialty occupation filings require a direct tie between your degree field and the role. If your degree is in mathematics or physics rather than computer science, gather course transcripts now to support USCIS's specialty occupation assessment.
Negotiate your start date around H-1B cap timelines
If you need a cap-subject H-1B, USCIS registration opens in March for an October 1 start. Confirm with your Apple recruiter early whether your role qualifies for a cap-exempt filing through a university partner, which removes the lottery dependency entirely.
Use Migrate Mate to identify open AI ML roles at Apple
Apple posts AI ML Engineer openings across multiple teams simultaneously and roles fill quickly. Use Migrate Mate to filter Apple's active visa-sponsoring positions so you're applying to roles where sponsorship is already confirmed rather than asking after the fact.
Understand Apple's PERM timing if you want a Green Card
Apple initiates PERM labor certification for EB-2 and EB-3 Green Card sponsorship, but the process typically begins after you've established yourself in a role. During offer negotiation, ask directly whether your position has an established track record of Green Card sponsorship.
Frequently Asked Questions
Does Apple sponsor H-1B visas for AI ML Engineers?
Yes, Apple sponsors H-1B visas for AI ML Engineers and has a consistent track record doing so. Apple also sponsors H-1B1 visas for Chilean and Singaporean nationals and E-3 visas for Australians, which can be advantageous since those categories bypass the H-1B lottery. If your role qualifies through a university partnership, a cap-exempt H-1B visa filing may also be an option worth discussing with Apple's immigration team.
How do I apply for AI ML Engineer jobs at Apple?
Apply directly through Apple's careers site and tailor your resume to emphasize on-device machine learning, model optimization, and hardware-software co-design since those skills align closely with Apple's product priorities. Migrate Mate lists Apple's active AI ML Engineer openings filtered by visa sponsorship, which lets you confirm sponsorship eligibility before investing time in an application. Apple's hiring process typically includes a recruiter screen, technical assessments, and multiple rounds with the hiring team.
Which visa types does Apple commonly use for AI ML Engineer roles?
Apple uses H-1B, E-3, H-1B1 visa, and TN visas for AI ML Engineers depending on your nationality. F-1 OPT and CPT are used for students and recent graduates earlier in the pipeline. For longer-term sponsorship, Apple also files EB-2 and EB-3 Green Card petitions through the PERM labor certification process with the DOL for eligible employees.
What qualifications does Apple expect for AI ML Engineer roles?
Apple's AI ML Engineer roles typically require a bachelor's degree or higher in computer science, electrical engineering, or a closely related field, with strong applied experience in machine learning frameworks such as PyTorch or JAX. For USCIS specialty occupation purposes, your degree field needs to directly relate to the role's duties. Apple's research-oriented positions often prefer a master's degree or PhD, particularly for roles involving neural architecture design or on-device model optimization.
How do I understand the visa process timeline when joining Apple?
Timeline depends heavily on which visa category applies to you. E-3 and TN visas can be obtained within weeks through consular processing. A cap-subject H-1B requires registration in March and an October 1 start at the earliest, so Apple would need to extend your OPT or bridge your status in the interim. USCIS premium processing, which Apple commonly uses, accelerates H-1B adjudication to 15 business days but does not change the cap start date.