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
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
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BS/MS/PhD in Computer Science or Electrical Engineering.
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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 289+ 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.