E-3 Visa Machine Learning Scientist Jobs
Machine Learning Scientist roles qualify for E-3 visa sponsorship as specialty occupations requiring at least a bachelor's degree in computer science, statistics, or a related field. The E-3 has no lottery and no annual cap, so Australian nationals can pursue U.S. positions year-round without competing for limited slots the way H-1B visa applicants do.
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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 1,389+ E-3 Visa Machine Learning Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new E-3 Visa Machine Learning Scientist Jobs.
Get Access To All JobsTips for Finding E-3 Visa Sponsorship as a Machine Learning Scientist
Frame your research portfolio for U.S. specialty occupation standards
DOL requires your role to meet specialty occupation criteria, meaning a specific degree field must be normal for the position. Document how your ML research, publications, or graduate work maps to a defined technical discipline, not just general data science experience.
Target employers with active LCA filing history in ML
Companies that have previously certified LCAs for machine learning or AI research roles already understand the E-3 visa process. Searching DOL's Foreign Labor Certification disclosure data by SOC code 15-2051 surfaces employers who have filed for similar positions before.
Find Machine Learning Scientist roles using Migrate Mate
Migrate Mate filters job listings by E-3 sponsorship eligibility, so you're not cold-applying to employers unfamiliar with Australian visa requirements. Use Migrate Mate's E-3 filing service to handle your LCA and visa paperwork once you have an offer.
Clarify your employer's LCA wage level before signing
DOL prevailing wage determinations for ML Scientists vary significantly by level. Confirm that your offered wage meets at least Level II requirements for your metro area before your employer submits the LCA, since a deficient wage certification will block your visa application.
Distinguish your PhD or honours research from general engineering work
Consular officers assess whether the offered role genuinely requires a specialist degree. If your background is research-heavy, bring documentation of published work, conference presentations, or specialised methods that separate the position from a standard software engineering role.
Time your consulate appointment around your employer's LCA certification
The E-3 consular application cannot proceed until your employer's LCA is certified by DOL, which currently averages around seven business days. Build that window into your start date negotiation so your visa appointment isn't scheduled before the certified LCA is in hand.
E-3 Visa Machine Learning Scientist: Frequently Asked Questions
How do I find Machine Learning Scientist jobs with E-3 visa sponsorship?
Migrate Mate is the recommended tool for this search. It surfaces Machine Learning Scientist roles at employers who are open to E-3 sponsorship, saving you from applying to companies unfamiliar with the visa. Because the E-3 has no lottery and no annual cap, any role that qualifies as a specialty occupation can be filled year-round, which expands the pool of willing sponsors compared to H-1B hiring.
How much does it cost to get an E-3 visa?
Migrate Mate's E-3 filing service covers the entire process for $499, including the Labor Condition Application, visa document preparation, and consulate appointment guidance. Traditional immigration lawyers charge $2,000–$5,000+ for the same work. The E-3 has less paperwork than most work visas, so paying thousands for legal help is usually unnecessary.
Does a Machine Learning Scientist role qualify as a specialty occupation for the E-3?
Yes, provided the position normally requires at least a bachelor's degree in a specific technical field such as computer science, statistics, applied mathematics, or a closely related discipline. Roles that accept any degree regardless of field, or that treat the degree as a general credential rather than a job-specific requirement, may not satisfy DOL's specialty occupation standard. Documenting the technical degree requirement in the job description strengthens the LCA.
How does the E-3 compare to the H-1B for Machine Learning Scientist positions?
The E-3 is significantly more predictable for Australian ML Scientists. The H-1B is subject to an annual cap and a random lottery, meaning a qualifying offer and petition can still be rejected by chance. The E-3 has a 10,500-slot annual allocation that has never been exhausted, so there is no lottery. Approved E-3 status lasts two years and renews indefinitely, and you can apply at the consulate within weeks of receiving an offer rather than waiting for an October start date.
Can I transfer my E-3 status if I move between machine learning roles or employers?
Yes, but each new employer must file a fresh LCA and your role must independently qualify as a specialty occupation. There is no portability rule that carries over from a previous E-3 employer the way AC21 works for H-1B holders. You should avoid a gap in authorised employment, and many practitioners recommend not resigning until the new LCA is certified and your visa documentation is updated.