Engineering Jobs at Apple with Visa Sponsorship
Engineering jobs at Apple span hardware, silicon, software systems, and beyond, with roles ranging from chip architecture to manufacturing process engineering. Apple has a strong track record of sponsoring work visas for qualified Engineering candidates, covering multiple visa categories to support both early-career and experienced hires.
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Get Access To All JobsINTRODUCTION
The On-Device Machine Learning team at Apple is responsible for enabling the Research to Production lifecycle of cutting-edge machine learning models that power magical user experiences on Apple's hardware and software platforms.
The team builds critical infrastructure that begins with onboarding the latest machine learning architectures to Apple devices, optimization toolkits to optimize these models to better suit the target devices, machine learning compilers and runtimes to execute these models as efficiently as possible, and the benchmarking, analysis and debugging toolchain needed to improve on new model iterations.
This infrastructure underpins most of Apple's critical machine learning workflows across Camera, Siri, Health, Vision, etc., and as such is an integral part of Apple Intelligence.
Our group is seeking an Engineering Manager to lead the Performance Tools and Services team, with a focus on the tools, services, and infrastructure that make on-device ML performance measurable, understandable, and improvable. The team is responsible for the frontend web services for introspecting ML models and their on-device execution, the backend web services that power them, and the on-device toolchain that gathers low-level performance data, associates it with high-level (PyTorch) framework-level ops, and reports it. The team is also responsible for the infrastructure for running ML inference across fleets of devices.
DESCRIPTION
We are building the first end-to-end developer experience for ML development that, by taking advantage of Apple's vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis.
This role focuses on giving ML developers fast, accurate, and actionable insight into how their models execute on Apple devices. We're looking for a manager that has proven experience in and passion for providing high quality developer tools and capabilities in the fast paced and dynamic space of ML.
As the manager in this role, you will lead a diverse team spanning full-stack web development, backend services, distributed systems, and low-level on-device performance tooling. You will partner with leaders across the organization and company to develop our platform while supporting clients internally and externally.
The role requires a solid technical understanding of ML execution on device, performance analysis and profiling, and the systems that connect low-level signals to framework-level (e.g., PyTorch) semantics.
Responsibilities
-
Leading and growing the team that builds the frontend web services for introspecting ML models and their on-device execution, the backend services that support them, and the on-device toolchain for gathering and reporting low-level performance data.
-
Driving future efforts to improve the “model authoring performance profiling improve model repeat“ workflow, making it faster and more insightful for ML developers.
-
Owning the infrastructure for running ML inference across fleets of devices, ensuring it is reliable, scalable, and produces trustworthy performance data.
-
Attracting, hiring, and guiding the career of talented ML, software, and tools engineers.
-
Working with cross functional partners to push the state-of-the-art of on-device ML functionality and performance.
MINIMUM QUALIFICATIONS
-
BS/MS/PhD in Computer Science or Electrical Engineering.
-
Two or more years of strong and validated management experience.
-
Knowledge of ML development and workflows, including at least one authoring framework experience (e.g., PyTorch).
-
Experience delivering web services and/or developer-facing tools, spanning frontend and backend.
-
Excellent communication skills.
-
Track record of creating clean software architectures, intuitive designs, and high-performance extensible software.
-
Solid programming skills in at least one of the following languages: Python, Swift, Objective-C, C/C++.
PREFERRED QUALIFICATIONS
-
Experience with on-device ML frameworks (Core ML, Win ML, ONNX, TF Lite or ExecuTorch).
-
Experience with performance profiling, benchmarking, and analysis tooling.
-
Experience building and operating infrastructure for running workloads across fleets of devices.
-
Experience associating low-level performance data with framework-level operations.
-
Experience with MLIR / LLVM compiler technologies.
PAY & BENEFITS
This posting is not for a specific job opening and by submitting your resume you are expressing interest in being contacted about this type of role at Apple in the future.
INTRODUCTION
The On-Device Machine Learning team at Apple is responsible for enabling the Research to Production lifecycle of cutting-edge machine learning models that power magical user experiences on Apple's hardware and software platforms.
The team builds critical infrastructure that begins with onboarding the latest machine learning architectures to Apple devices, optimization toolkits to optimize these models to better suit the target devices, machine learning compilers and runtimes to execute these models as efficiently as possible, and the benchmarking, analysis and debugging toolchain needed to improve on new model iterations.
This infrastructure underpins most of Apple's critical machine learning workflows across Camera, Siri, Health, Vision, etc., and as such is an integral part of Apple Intelligence.
Our group is seeking an Engineering Manager to lead the Performance Tools and Services team, with a focus on the tools, services, and infrastructure that make on-device ML performance measurable, understandable, and improvable. The team is responsible for the frontend web services for introspecting ML models and their on-device execution, the backend web services that power them, and the on-device toolchain that gathers low-level performance data, associates it with high-level (PyTorch) framework-level ops, and reports it. The team is also responsible for the infrastructure for running ML inference across fleets of devices.
DESCRIPTION
We are building the first end-to-end developer experience for ML development that, by taking advantage of Apple's vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis.
This role focuses on giving ML developers fast, accurate, and actionable insight into how their models execute on Apple devices. We're looking for a manager that has proven experience in and passion for providing high quality developer tools and capabilities in the fast paced and dynamic space of ML.
As the manager in this role, you will lead a diverse team spanning full-stack web development, backend services, distributed systems, and low-level on-device performance tooling. You will partner with leaders across the organization and company to develop our platform while supporting clients internally and externally.
The role requires a solid technical understanding of ML execution on device, performance analysis and profiling, and the systems that connect low-level signals to framework-level (e.g., PyTorch) semantics.
Responsibilities
-
Leading and growing the team that builds the frontend web services for introspecting ML models and their on-device execution, the backend services that support them, and the on-device toolchain for gathering and reporting low-level performance data.
-
Driving future efforts to improve the “model authoring performance profiling improve model repeat“ workflow, making it faster and more insightful for ML developers.
-
Owning the infrastructure for running ML inference across fleets of devices, ensuring it is reliable, scalable, and produces trustworthy performance data.
-
Attracting, hiring, and guiding the career of talented ML, software, and tools engineers.
-
Working with cross functional partners to push the state-of-the-art of on-device ML functionality and performance.
MINIMUM QUALIFICATIONS
-
BS/MS/PhD in Computer Science or Electrical Engineering.
-
Two or more years of strong and validated management experience.
-
Knowledge of ML development and workflows, including at least one authoring framework experience (e.g., PyTorch).
-
Experience delivering web services and/or developer-facing tools, spanning frontend and backend.
-
Excellent communication skills.
-
Track record of creating clean software architectures, intuitive designs, and high-performance extensible software.
-
Solid programming skills in at least one of the following languages: Python, Swift, Objective-C, C/C++.
PREFERRED QUALIFICATIONS
-
Experience with on-device ML frameworks (Core ML, Win ML, ONNX, TF Lite or ExecuTorch).
-
Experience with performance profiling, benchmarking, and analysis tooling.
-
Experience building and operating infrastructure for running workloads across fleets of devices.
-
Experience associating low-level performance data with framework-level operations.
-
Experience with MLIR / LLVM compiler technologies.
PAY & BENEFITS
This posting is not for a specific job opening and by submitting your resume you are expressing interest in being contacted about this type of role at Apple in the future.
See all 290+ Engineering Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Engineering Jobs at Apple.
Get Access To All JobsTips for Finding Engineering Jobs at Apple
Align your degree to Apple's specialty occupation standard
Apple's Engineering requisitions typically require a degree in a specific engineering discipline, not just any STEM field. A general science degree may not satisfy USCIS specialty occupation requirements for a hardware or silicon role, so frame your credentials precisely.
Target Apple's recurring Engineering hiring cycles
Apple posts Engineering roles heavily in the months before the H-1B registration window opens in March. Timing your application to land an offer in January or February gives your employer the maximum runway to prepare your petition before the cap deadline.
Distinguish yourself across Apple's core engineering pillars
Apple hires across silicon design, RF engineering, camera systems, and manufacturing process engineering. Tailoring your resume to one specific pillar rather than applying broadly across all Engineering roles significantly improves your chances of reaching a technical interview.
Confirm Apple's E-3 or TN eligibility before your interview
If you're an Australian or Canadian citizen, Apple sponsors the E-3 and TN visa respectively, both of which bypass the H-1B lottery entirely. Confirm your citizenship eligibility upfront so Apple's immigration team can route your petition correctly from the start.
Use Migrate Mate to filter open Engineering roles at Apple by visa type
Not every Apple Engineering listing is open to sponsored candidates. Use Migrate Mate to filter roles specifically tagged for sponsorship, so you're only spending time on applications where your visa situation is already accounted for.
Request premium processing if your OPT window is closing
If you're on F-1 OPT and your authorization end date is within six months of an offer, ask Apple's immigration team early whether they'll file with USCIS premium processing. The standard H-1B adjudication timeline can outlast a narrow OPT window.
Frequently Asked Questions
Does Apple sponsor H-1B visas for Engineers?
Yes, Apple sponsors H-1B visas for Engineering roles across its hardware, silicon, and software systems teams. Apple works with experienced immigration counsel to handle the full petition process, including Labor Condition Application filing with the DOL. Because the H-1B is subject to an annual lottery, Apple typically targets offer timelines that allow petition submission before the March registration window.
How do I apply for Engineering jobs at Apple?
You can apply directly through Apple's careers site, or browse Apple's sponsored Engineering roles on Migrate Mate, which filters specifically for positions open to visa sponsorship. Apple's Engineering hiring process generally includes a recruiter screen, technical phone interviews, and an on-site or virtual loop. Roles in hardware and silicon tend to require a portfolio of project work or published research in addition to standard interviews.
Which visa types does Apple commonly sponsor for Engineering roles?
Apple sponsors the H-1B, H-1B1 visa (for Chilean and Singaporean nationals), E-3 visa (for Australian citizens), and TN visa (for Canadian and Mexican nationals) for Engineering positions. For permanent residency, Apple supports EB-2 and EB-3 Green Card pathways. Apple also participates in F-1 OPT and CPT programs, making it accessible to recent graduates from U.S. universities before they require a full work visa.
What qualifications does Apple expect for sponsored Engineering roles?
Apple's Engineering roles typically require a bachelor's degree at minimum in a directly relevant discipline such as electrical engineering, computer engineering, mechanical engineering, or materials science. Many roles, particularly in silicon architecture or RF systems, prefer a master's degree or equivalent research experience. USCIS requires that the role qualify as a specialty occupation, meaning the specific degree field must align directly with the job duties.
How do I plan my timeline for an Apple Engineering visa sponsorship?
If you're targeting an H-1B, Apple needs to register you in the USCIS lottery by late March, with employment typically starting October 1. That means securing an offer by January or February is practical. For cap-exempt pathways like the E-3 or TN, there's no annual deadline, and Apple can file year-round, often with faster processing since no lottery is involved.