E-3 Visa AI ML Intern Jobs
AI ML Intern roles in the U.S. qualify for E-3 visa sponsorship when the position requires a bachelor's degree in computer science, data science, or a related field. The E-3 has no lottery and no annual cap, so Australian nationals can secure internship roles on a predictable timeline without competing for limited slots.
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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 1,388+ E-3 Visa AI ML Intern Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new E-3 Visa AI ML Intern Jobs.
Get Access To All JobsTips for Finding E-3 Visa Sponsorship as an AI ML Intern
Frame your degree field precisely
E-3 visa eligibility requires a direct connection between your degree and the role. A computer science or data science degree maps cleanly to AI/ML intern positions, but a general IT or business degree needs supporting documentation linking your coursework to machine learning applications.
Target employers enrolled in E-Verify
Internship sponsors must file an LCA with DOL before you can apply. Employers already enrolled in E-Verify have completed federal compliance steps that signal familiarity with visa-sponsored hiring, making the LCA process smoother for both sides.
Negotiate your start date around LCA timing
DOL typically certifies LCAs within seven business days, but your employer needs to request certification before you can book your consulate appointment. Build at least two to three weeks of buffer between your offer acceptance and your intended start date.
Use Migrate Mate's E-3 filing service for intern paperwork
Intern roles add complexity because prevailing wage determinations for entry-level positions differ from full-time roles. Use Migrate Mate's E-3 filing service to handle your LCA and visa paperwork so wage level classifications and job duty descriptions are filed correctly from the start.
Clarify whether the internship converts to full-time
E-3 status is employer-specific. If your internship has a conversion pathway, confirm your employer will file a new LCA for the full-time role. Starting that process before your intern E-3 expires avoids a gap in authorized status.
Prepare academic transcripts with official translations
Australian three-year bachelor's degrees are generally accepted as equivalent to U.S. four-year degrees for E-3 purposes, but consular officers may request academic records. Have certified transcripts ready before your interview to address any degree equivalency questions on the spot.
E-3 Visa AI ML Intern: Frequently Asked Questions
How do I find AI ML Intern jobs with E-3 visa sponsorship?
Migrate Mate is built specifically for Australian professionals searching for E-3 visa-sponsored roles in the U.S. You can filter by job title and see which employers are actively hiring interns on E-3 sponsorship, without sorting through listings that don't offer visa support or that require H-1B lottery selection.
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 an AI ML Intern role qualify as a specialty occupation for E-3?
Yes, if the position requires a bachelor's degree or higher in a specific field such as computer science, data science, mathematics, or electrical engineering. The key is that the role must theoretically and practically require that degree. Internships structured as generalist tech support or non-technical rotations may not meet the specialty occupation standard and could face scrutiny at the consulate.
How does the E-3 compare to the H-1B for AI ML Intern roles?
The E-3 has no annual cap and no lottery, so you can apply at any time of year and start as soon as your visa is approved. H-1B selection happens once per year in April and covers roughly one in four registrants. For an internship with a defined start date, the E-3 is the only reliable path for Australian nationals who need predictable timing.
Can I convert my E-3 intern status to a full-time E-3 after graduation?
Yes, but your employer must file a new LCA with DOL for the full-time role because the job duties, wage level, and employment terms will differ from your internship. USCIS treats each E-3 petition as employer-specific, so the new LCA and visa application must accurately reflect the full-time position. Starting that process two to three months before your internship ends prevents a gap in status.