AI ML Engineering Jobs at Apple with Visa Sponsorship
AI ML Engineering jobs at Apple involve building some of the company's most ambitious AI and machine learning work into its hardware and software ecosystem, with teams spanning roles from research scientists to production ML engineers. Apple has a consistent track record of sponsoring work visas for qualified AI ML Engineering candidates across multiple visa categories.
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Get Access To All JobsJoin the team redefining what a deeply personal and integrated assistant can be.
As part of the Siri organization, you will help shape one of the world's most widely used AI assistants, powered by our next-generation of Apple Intelligence, with capabilities like personal context understanding and on-screen awareness, built with privacy from the ground up. Your work will have direct, meaningful impact for users across iOS, iPadOS, macOS, watchOS, and visionOS.
This is a rare opportunity to build at the intersection of cutting-edge AI and human-centered design, shipping technology that is centered around users and their needs.
Description
We are the team building products for voice, dictation and other audio products at Apple. These are multimodal models that power Siri on-device speech features, and the next generation of audio experiences across our platforms. Our researchers and modeling engineers train models, iterate on data mixtures spanning conductor backed Siri telemetry to synthetic voice corpora, and stack supervised fine-tuning, LoRA adapter training, and reinforcement learning into pipelines that produce the adapters, tokenizers and detokenizers.
You’ll join a small group of production automation engineers whose mandate is to turn the operational substrate underneath foundation model training into a reliable, observable, self-serve system. The work spans python, shell tooling, cloud platform integration, internal CLI design, and close partnership with the product and research teams you are enabling.
Responsibilities
-
Own the end-to-end model lifecycle building model pipelines, integrating with other Apple frameworks to enable rapid model iteration, staging promotion, production rollout and deprecation.
-
Design and operate agent-based automation pipelines for ML models where agents own decision logic at each gate and humans approve only at defined escalation points.
-
Develop multi-agent workflows using LLM-native tooling for on-device evaluation, regression triage, release readiness decisions, and automated root cause analysis.
-
Own the launch tooling to build and improve the shell scripts and CLI commands that turn a config-name and a dataset into a running training job - across SFT, LoRA adapter, and RL phases.
Minimum Qualifications
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Strong software engineering fundamentals; comfortable in Python and Bash, comfortable reading and refactoring large internal codebases.
-
5+ years experience in Machine Learning Operations.
-
Production experience with one or more cloud ML platforms (GCP TPU, AWS GPU clusters, Kubernetes-backed training infra) including submitting jobs, debugging schedulers, working around quota systems.
-
Familiarity with the ML training lifecycle: data preprocessing pipelines, distributed training, checkpoint formats, multi-slice / multi-region considerations.
-
Experience with infrastructure-as-code, CLI tool design, and developer ergonomics. You've shipped tools that other engineers actually use.
-
Bias toward observability and reliability.
-
Comfortable working across team boundaries: you'll partner with researchers, product and infra teams.
Preferred Qualifications
-
Bachelors degree in Computer Science or equivalent technical discipline.
-
Hands-on with JAX, XLA, or large-model training stacks or equivalent.
-
Experience with multi-slice TPU training and cross-region GCS / S3-compatible storage.
-
Background in MLOps tools: model registries, feature stores, experiment trackers, reward-model serving for RL.
-
Prior work simplifying onboarding and access provisioning (Apple Access Manager, AWS IAM at scale, or equivalent).
-
Experience writing Claude Code / agent skills, runbooks, or other LLM-assisted developer tooling.
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 $181,100 and $318,400, 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.
Join the team redefining what a deeply personal and integrated assistant can be.
As part of the Siri organization, you will help shape one of the world's most widely used AI assistants, powered by our next-generation of Apple Intelligence, with capabilities like personal context understanding and on-screen awareness, built with privacy from the ground up. Your work will have direct, meaningful impact for users across iOS, iPadOS, macOS, watchOS, and visionOS.
This is a rare opportunity to build at the intersection of cutting-edge AI and human-centered design, shipping technology that is centered around users and their needs.
Description
We are the team building products for voice, dictation and other audio products at Apple. These are multimodal models that power Siri on-device speech features, and the next generation of audio experiences across our platforms. Our researchers and modeling engineers train models, iterate on data mixtures spanning conductor backed Siri telemetry to synthetic voice corpora, and stack supervised fine-tuning, LoRA adapter training, and reinforcement learning into pipelines that produce the adapters, tokenizers and detokenizers.
You’ll join a small group of production automation engineers whose mandate is to turn the operational substrate underneath foundation model training into a reliable, observable, self-serve system. The work spans python, shell tooling, cloud platform integration, internal CLI design, and close partnership with the product and research teams you are enabling.
Responsibilities
-
Own the end-to-end model lifecycle building model pipelines, integrating with other Apple frameworks to enable rapid model iteration, staging promotion, production rollout and deprecation.
-
Design and operate agent-based automation pipelines for ML models where agents own decision logic at each gate and humans approve only at defined escalation points.
-
Develop multi-agent workflows using LLM-native tooling for on-device evaluation, regression triage, release readiness decisions, and automated root cause analysis.
-
Own the launch tooling to build and improve the shell scripts and CLI commands that turn a config-name and a dataset into a running training job - across SFT, LoRA adapter, and RL phases.
Minimum Qualifications
-
Strong software engineering fundamentals; comfortable in Python and Bash, comfortable reading and refactoring large internal codebases.
-
5+ years experience in Machine Learning Operations.
-
Production experience with one or more cloud ML platforms (GCP TPU, AWS GPU clusters, Kubernetes-backed training infra) including submitting jobs, debugging schedulers, working around quota systems.
-
Familiarity with the ML training lifecycle: data preprocessing pipelines, distributed training, checkpoint formats, multi-slice / multi-region considerations.
-
Experience with infrastructure-as-code, CLI tool design, and developer ergonomics. You've shipped tools that other engineers actually use.
-
Bias toward observability and reliability.
-
Comfortable working across team boundaries: you'll partner with researchers, product and infra teams.
Preferred Qualifications
-
Bachelors degree in Computer Science or equivalent technical discipline.
-
Hands-on with JAX, XLA, or large-model training stacks or equivalent.
-
Experience with multi-slice TPU training and cross-region GCS / S3-compatible storage.
-
Background in MLOps tools: model registries, feature stores, experiment trackers, reward-model serving for RL.
-
Prior work simplifying onboarding and access provisioning (Apple Access Manager, AWS IAM at scale, or equivalent).
-
Experience writing Claude Code / agent skills, runbooks, or other LLM-assisted developer tooling.
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 $181,100 and $318,400, 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 295+ AI ML Engineering Jobs at Apple
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI ML Engineering Jobs at Apple.
Get Access To All JobsTips for Finding AI ML Engineering Jobs at Apple
Align your portfolio to Apple's on-device focus
Apple prioritizes ML work that runs efficiently on its own silicon, including Neural Engine optimization and Core ML integration. Demonstrating experience with model compression, quantization, or edge inference directly signals relevance to their engineering priorities.
Target teams building Apple Intelligence features
Apple's AI ML Engineering openings cluster around Siri, Photos, Health, and the Apple Intelligence platform. Reviewing recently shipped product features helps you identify which internal teams are actively hiring and tailor your application accordingly.
Clarify your visa category before the offer stage
Apple sponsors H-1B, E-3, TN, and F-1 OPT depending on your nationality and status. Confirm which category applies to you early in recruiter conversations so there's no ambiguity when the offer and legal team processes begin.
Prepare for Apple's multi-round technical interviews
Apple's ML interview loop typically includes coding, ML system design, and a domain-specific research discussion. Having published work, open-source contributions, or documented production ML systems strengthens your case at every round.
Understand OPT timing relative to Apple's hiring cycles
If you're on F-1 OPT, verify your authorization end date before accepting an offer. Apple's onboarding timelines can run six to eight weeks, and STEM OPT extension applications must be filed through your DSO before your initial OPT expires.
Use Migrate Mate to find active AI ML Engineering roles at Apple
Apple posts AI ML Engineering roles across multiple teams simultaneously, and openings move quickly. Use Migrate Mate to browse current positions filtered specifically for visa-sponsored roles so you're applying to openings where sponsorship is already confirmed.
Frequently Asked Questions
Does Apple sponsor H-1B visas for AI ML Engineers?
Yes, Apple sponsors H-1B visas for AI ML Engineering roles. Because the H-1B is subject to an annual lottery, Apple typically submits registrations in March for the following fiscal year. If you're already on H-1B with another employer, Apple can file an H-1B transfer, which lets you start without waiting for a new cap slot.
Which visa types does Apple commonly sponsor for AI ML Engineering positions?
Apple sponsors several visa categories for AI ML Engineering roles depending on your nationality and current status. Australian citizens can use the E-3 visa, Canadian and Mexican nationals can qualify under TN visa, and F-1 graduates can begin on OPT or STEM OPT extension. For longer-term sponsorship, Apple also supports EB-2 and EB-3 Green Card pathways for qualifying engineers.
What qualifications does Apple expect for AI ML Engineering roles?
Apple's AI ML Engineering roles typically require a bachelor's degree in computer science, electrical engineering, or a related field, with a master's or PhD preferred for research-adjacent positions. Hands-on experience with frameworks like PyTorch or JAX, familiarity with Apple's Core ML ecosystem, and demonstrated work on production ML systems at scale are commonly expected across levels.
How do I apply for AI ML Engineering jobs at Apple?
You can apply directly through Apple's careers site or find visa-sponsored openings through Migrate Mate, which filters specifically for roles where sponsorship is confirmed. Apple's process for ML roles typically involves a recruiter screen, a technical phone interview, and a multi-round onsite or virtual loop covering coding, ML system design, and a domain discussion. Response timelines after applying range from two to six weeks depending on the team.
How do I time my Apple job search around H-1B cap deadlines?
The H-1B registration window opens in early March each year, with USCIS selecting registrations by late March. To be included in that cycle, you need an offer and a registered employer before the window closes. Targeting Apple roles between October and February gives you the best chance of securing an offer in time for your employer to register you before the deadline.