Machine Learning Scientist Jobs at Apple with Visa Sponsorship
Machine Learning Scientist jobs at Apple involve building some of the company's most consequential research teams, with roles spanning on-device intelligence, natural language processing, and computer vision. Apple has a well-established sponsorship track record for this function and supports multiple visa pathways for international candidates.
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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 281+ Machine Learning Scientist Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Scientist Jobs at Apple.
Get Access To All JobsTips for Finding Machine Learning Scientist Jobs at Apple
Align your research portfolio to Apple's ML focus areas
Apple prioritizes on-device ML, privacy-preserving machine learning, and neural engine optimization. Tailoring your published work, GitHub projects, or patents to these areas signals fit before your resume reaches a recruiter.
Target teams through Apple's research publication record
Apple ML researchers publish under groups like Siri, Core ML, and Vision. Identifying specific teams via their public papers helps you name the right organization in your application and network toward the right hiring manager.
Verify your visa type early in the interview process
Apple sponsors H-1B, E-3, TN, and F-1 OPT among other categories. If you're nearing the end of OPT, confirm with the recruiter whether Apple's legal team can file before your authorization expires, since processing timelines matter.
Prepare a degree equivalency letter if your credential is non-U.S.
For H-1B specialty occupation petitions, USCIS scrutinizes foreign degree equivalency. Having a credential evaluation from a NACES-member organization ready before offer stage avoids delays once Apple's immigration counsel begins the I-129 filing.
Use Migrate Mate to filter open Machine Learning Scientist roles by visa type
Sponsorship eligibility varies by role and team even within Apple. Use Migrate Mate to surface active postings filtered to your specific visa category so you're applying to positions Apple is actively sponsoring for that function.
Request a start date that accommodates DOL and USCIS timelines
Once Apple's legal team initiates the H-1B process, the Labor Condition Application must clear DOL before the I-129 is filed with USCIS. Negotiating a start date at least 90 days out reduces the risk of a gap in work authorization.
Frequently Asked Questions
Does Apple sponsor H-1B visas for Machine Learning Scientists?
Yes, Apple sponsors H-1B visas for Machine Learning Scientists. The company works with in-house immigration counsel to manage LCA filings with the DOL and I-129 petitions with USCIS. Because Machine Learning Scientist roles qualify as specialty occupations requiring at minimum a bachelor's degree in a directly related field like computer science or statistics, they're well-suited for H-1B sponsorship.
How do I apply for Machine Learning Scientist jobs at Apple?
Applications go through Apple's careers portal at jobs.apple.com. Roles are listed under Research and Machine Learning or within specific product organizations like Siri, Core ML, or Health. You can also find and filter open Machine Learning Scientist positions at Apple by visa type on Migrate Mate, which surfaces active sponsorship-eligible postings in one place.
Which visa types does Apple commonly sponsor for Machine Learning Scientist roles?
Apple sponsors H-1B and H-1B1 visas for most international candidates in this function. Australian citizens are eligible for the E-3 visa, which has no lottery and is processed separately from the H-1B cap. Canadian and Mexican nationals may qualify under TN visa status. F-1 OPT and CPT are also supported for students in qualifying programs, and Apple files EB-2 and EB-3 petitions for permanent residence.
What qualifications does Apple expect for Machine Learning Scientist roles?
Most Machine Learning Scientist postings at Apple require a PhD or a master's degree with substantial research experience in machine learning, computer science, or a closely related quantitative field. Apple's teams value publication records, experience with large-scale model training, and proficiency in frameworks like PyTorch or JAX. Roles focused on on-device ML also expect familiarity with model compression, quantization, or neural architecture search.
How do I estimate the timeline from offer to work authorization at Apple?
After accepting an offer, Apple's immigration team typically initiates the LCA filing with DOL, which takes around seven business days under standard processing. The I-129 H-1B petition then goes to USCIS. Standard processing takes several months, but premium processing reduces USCIS adjudication to 15 business days. For E-3 visa applicants, consular processing in Australia can move faster. Plan on at least 60 to 90 days from offer to start date for most pathways.