TN Visa Machine Learning Scientist Jobs
Machine Learning Scientist roles qualify for TN visa sponsorship under the USMCA's Computer Systems Analyst category when the position requires a bachelor's degree or higher in computer science, mathematics, or a related field. Canadian citizens can apply at the border or a U.S. consulate without a cap; Mexican citizens are subject to a 5,500 annual allocation.
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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
-
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 TN Visa Machine Learning Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new TN Visa Machine Learning Scientist Jobs.
Get Access To All JobsTips for Finding TN Visa Sponsorship as a Machine Learning Scientist
Frame your credentials around specialty occupation
TN visa approval for ML Scientist roles hinges on demonstrating that your degree directly relates to the job. A mathematics or statistics degree supporting a deep learning role is a stronger credential match than a general computer science degree for an ambiguous 'AI researcher' title.
Target employers with recent visa filing experience
Employers with recent visa filings for ML or data science roles have demonstrated experience with work visa sponsorship. Identify companies with a track record of visa sponsorship by reviewing their recent filings—this signals they understand the sponsorship process and may be open to supporting TN candidates with the right qualifications.
Request a support letter that specifies ML tasks
Your employer's TN support letter must describe duties that map to a recognized USMCA profession. Ask HR to list specific responsibilities like model training, algorithm development, or statistical inference rather than vague phrases like 'working on AI projects.'
Use Migrate Mate to find TN-ready ML employers
Searching broadly wastes time on employers unfamiliar with TN sponsorship. Migrate Mate filters Machine Learning Scientist roles by TN visa compatibility, so you're reaching out to companies already equipped to move quickly on an offer.
Prepare for CBP scrutiny on job title alignment
Canadian citizens processed at the port of entry face a CBP officer who evaluates your title against the USMCA profession list on the spot. If your offer letter says 'ML Engineer' instead of 'Computer Systems Analyst,' bring documentation clarifying the role's analytical and systems focus.
Negotiate a start date that accounts for Mexican TN timelines
Mexican nationals must schedule a consular interview, which can take several weeks depending on the nearest U.S. consulate's availability. Build at least six to eight weeks between your signed offer and your proposed start date to avoid a gap between offer acceptance and authorized work.
Machine Learning Scientist TN Visa: Frequently Asked Questions
Does a Machine Learning Scientist role qualify for TN visa status?
Yes, provided the position requires a bachelor's degree or higher in a qualifying field such as computer science, mathematics, statistics, or engineering, and the duties center on analytical or systems work. CBP typically classifies ML Scientist roles under the Computer Systems Analyst profession on the USMCA occupation list. Job titles that blur into software engineering or product management can create issues, so the offer letter's duty description carries significant weight.
How does TN visa sponsorship compare to H-1B for Machine Learning Scientists?
TN has no annual lottery and no cap for Canadian citizens, so you can secure status any time of year without waiting for an April registration window. H-1B visa selection is random and limited to 85,000 slots annually, meaning qualified candidates are routinely left out. For Mexican nationals, the TN allocation is 5,500 per year, which is far smaller but still processes without a lottery. TN also renews indefinitely in three-year increments as long as you maintain qualifying employment.
What documents does my employer need to provide for my TN application?
Your employer must supply a signed support letter on company letterhead that states your job title, a description of duties tied to a recognized USMCA profession, your intended start date, and confirmation that the position requires a qualifying degree. You provide proof of citizenship and your academic credentials. For Canadian citizens applying at a port of entry, these documents go directly to CBP. Mexican nationals submit them as part of the consular visa packet.
Where can I find Machine Learning Scientist jobs that already support TN visa sponsorship?
Migrate Mate is built specifically for Canadian and Mexican professionals seeking TN-compatible roles in the U.S. It filters job listings by visa sponsorship type, so you're not sifting through postings from companies unfamiliar with TN status. Starting your search there reduces back-and-forth with employers who aren't prepared to issue a compliant support letter or move quickly through the filing process.
Can I switch employers while on TN status as an ML Scientist?
Yes, but you cannot begin work for the new employer before your new TN is approved. Canadian citizens can apply for a new TN at a port of entry or by filing a change of status petition with USCIS. There is no grace period that permits you to work during the transition, so timing your resignation and your new TN approval carefully is essential. Mexican nationals need a new visa stamp from a U.S. consulate before starting with the new employer.