STEM OPT Applied AI Engineer Jobs
Applied AI Engineer roles sit squarely within STEM degree categories that qualify for the 24-month STEM OPT extension, giving you up to 36 months of F-1 work authorization. Every employer you work for must be enrolled in E-Verify and sign a formal training plan with your DSO before your extension starts.
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Get Access To All JobsSUMMARY
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. It runs on our next generation of Apple Intelligence, with capabilities like personal context understanding and on-screen awareness, and it is built with privacy from the ground up. We build the harness, the foundation that turns a model into an assistant that can act. This is a systems engineering role for people who understand how large language models behave.
DESCRIPTION
A model can't act on its own. The harness runs the agent loop, carries context and tools to the model, executes the tool calls it makes, and streams results back reliably. It spans models running on device and larger models in Private Cloud Compute. It handles everything from single-turn requests to long multi-step tasks that span apps, survive interruptions, and resume cleanly. We're looking for a strong systems engineer who is fluent in how LLMs behave. The work is real-time and resource-constrained: responses must start fast enough for a voice assistant to feel instant, under tight latency, memory, and power limits on everything from Mac and iPhone to Apple Watch. Failures rarely have a single cause. In a typical week you might track down why a streamed response stalls, make tool calls cancel cleanly when the user interrupts, or replay a failed request to tell whether the model, the context, or the runtime was at fault. Every change to the harness changes how the model behaves, so we measure our work with evals, not just tests. You'll join the team that owns the core runtime and work alongside senior engineers and researchers. You'll also partner closely with the modeling, tools, and context teams and with app and framework teams across Apple. You'll take features from design through production and grow your ownership of the system over time. You'll use agent harnesses every day while building one for an assistant used by hundreds of millions of people.
MINIMUM QUALIFICATIONS
- Bachelor's degree in Computer Science or a related field, with 2+ years of industry experience
- Strong programming skills in a systems language such as Swift, C++, Rust, Objective-C, or Go
- Solid foundation in concurrency, inter-process communication, and performance optimization
- Hands-on experience building LLM-powered systems such as agents, tool calling, or prompt and context design, through professional work or substantial personal projects
- Daily use of agentic coding tools such as Claude Code, Codex, or Pi, with informed opinions on what makes their harnesses succeed or fail
- Ability to communicate clearly and make progress on ambiguous problems
PREFERRED QUALIFICATIONS
- Experience with Swift and Apple platform development
- Experience building agent harnesses, orchestration frameworks, or multi-step tool-use systems
- Experience with model inference integration, streaming protocols, or latency-sensitive client-server systems
- Experience using evals to diagnose and improve LLM behavior
- Experience designing APIs or platforms adopted by other engineering teams
- Familiarity with privacy and security engineering in production systems
- Active engagement with current research and practice in agent harness design, such as context engineering, tool use, and long-horizon agents, with a record of turning new ideas into practical improvements
COMPENSATION
- Base pay range for this role is between $150,400 and $277,600, 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.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.
At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Apple accepts applications to this posting on an ongoing basis.
SUMMARY
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. It runs on our next generation of Apple Intelligence, with capabilities like personal context understanding and on-screen awareness, and it is built with privacy from the ground up. We build the harness, the foundation that turns a model into an assistant that can act. This is a systems engineering role for people who understand how large language models behave.
DESCRIPTION
A model can't act on its own. The harness runs the agent loop, carries context and tools to the model, executes the tool calls it makes, and streams results back reliably. It spans models running on device and larger models in Private Cloud Compute. It handles everything from single-turn requests to long multi-step tasks that span apps, survive interruptions, and resume cleanly. We're looking for a strong systems engineer who is fluent in how LLMs behave. The work is real-time and resource-constrained: responses must start fast enough for a voice assistant to feel instant, under tight latency, memory, and power limits on everything from Mac and iPhone to Apple Watch. Failures rarely have a single cause. In a typical week you might track down why a streamed response stalls, make tool calls cancel cleanly when the user interrupts, or replay a failed request to tell whether the model, the context, or the runtime was at fault. Every change to the harness changes how the model behaves, so we measure our work with evals, not just tests. You'll join the team that owns the core runtime and work alongside senior engineers and researchers. You'll also partner closely with the modeling, tools, and context teams and with app and framework teams across Apple. You'll take features from design through production and grow your ownership of the system over time. You'll use agent harnesses every day while building one for an assistant used by hundreds of millions of people.
MINIMUM QUALIFICATIONS
- Bachelor's degree in Computer Science or a related field, with 2+ years of industry experience
- Strong programming skills in a systems language such as Swift, C++, Rust, Objective-C, or Go
- Solid foundation in concurrency, inter-process communication, and performance optimization
- Hands-on experience building LLM-powered systems such as agents, tool calling, or prompt and context design, through professional work or substantial personal projects
- Daily use of agentic coding tools such as Claude Code, Codex, or Pi, with informed opinions on what makes their harnesses succeed or fail
- Ability to communicate clearly and make progress on ambiguous problems
PREFERRED QUALIFICATIONS
- Experience with Swift and Apple platform development
- Experience building agent harnesses, orchestration frameworks, or multi-step tool-use systems
- Experience with model inference integration, streaming protocols, or latency-sensitive client-server systems
- Experience using evals to diagnose and improve LLM behavior
- Experience designing APIs or platforms adopted by other engineering teams
- Familiarity with privacy and security engineering in production systems
- Active engagement with current research and practice in agent harness design, such as context engineering, tool use, and long-horizon agents, with a record of turning new ideas into practical improvements
COMPENSATION
- Base pay range for this role is between $150,400 and $277,600, 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.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.
At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Apple accepts applications to this posting on an ongoing basis.
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Get Access To All JobsTips for Finding STEM OPT Authorization as an Applied AI Engineer
Confirm your CIP code qualifies first
Check that your degree's Classification of Instructional Programs code appears on the USCIS STEM Designated Degree Program List before applying. Computer science, electrical engineering, and data science CIP codes typically qualify, but applied mathematics or interdisciplinary programs sometimes don't.
Verify E-Verify enrollment before accepting offers
Search the E-Verify employer search tool to confirm any company is actively enrolled, not just registered. Enrollment status can lapse, and accepting an offer from an unenrolled employer invalidates your STEM OPT extension before it begins.
Frame your I-983 training plan around AI deliverables
Work with your DSO to list specific model training tasks, ML pipeline responsibilities, and evaluation benchmarks in your I-983. Vague descriptions like 'software development' create compliance risk during ICE site visits; AI-specific objectives tied to your degree field do not.
Target teams with dedicated ML infrastructure budgets
Applied AI Engineer roles at companies without production ML systems often convert to generalist software roles over time, which can undermine the degree-field connection USCIS requires. Look for teams running inference at scale or maintaining model registries as a sign of genuine AI practice.
Use Migrate Mate to filter for E-Verify employers hiring OPT students
Migrate Mate lets you search Applied AI Engineer openings filtered to employers already enrolled in E-Verify and with documented OPT hiring history, cutting the manual verification step out of your job search entirely.
Start your H-1B cap-gap timeline from day one
If your STEM OPT end date falls after April 1, file your H-1B visa registration before your OPT expires. A timely-filed H-1B petition triggers cap-gap protection, letting you keep working under the same employer without a gap in authorization.
Frequently Asked Questions
Does an Applied AI Engineer role qualify for the STEM OPT extension?
Yes, if your underlying degree carries a qualifying CIP code. Computer science, electrical engineering, statistics, and data science programs typically appear on the USCIS STEM Designated Degree Program List. The role itself also needs to directly relate to that degree field, so a job focused on building, training, or deploying AI models fits cleanly. Confirm your specific CIP code with your DSO before filing.
What E-Verify steps does my employer need to complete for my STEM OPT?
Your employer must be actively enrolled in E-Verify before your STEM OPT extension start date. Enrollment alone isn't enough; the company must also sign the I-983 training plan with you and your DSO, report material changes to your role within five business days, and cooperate with any ICE site visit. You can confirm active enrollment status through the E-Verify employer search tool before signing an offer.
What goes into the I-983 training plan for an Applied AI Engineer?
The I-983 must describe specific learning objectives tied to your degree field, not just your job title. For an Applied AI Engineer, that means listing concrete deliverables: model architecture decisions, dataset pipeline ownership, evaluation framework development, or deployment responsibilities. Generic software tasks weaken the connection to your STEM degree and create compliance exposure. Your DSO reviews and co-signs the plan before ICE and SEVP receive it.
How does cap-gap protection work if my STEM OPT expires during H-1B processing?
Cap-gap automatically extends your work authorization if your employer files a timely H-1B petition before your OPT EAD expires. The extension runs through September 30 of the fiscal year the H-1B is filed for. You continue working for the same E-Verify employer under the same role without interruption. USCIS issues a cap-gap receipt notice confirming your continued authorization.
Where can I find Applied AI Engineer jobs with employers already enrolled in E-Verify?
Migrate Mate filters Applied AI Engineer listings to employers enrolled in E-Verify and with a history of hiring F-1 OPT students, so you're not manually cross-referencing the E-Verify employer search against job postings. You can also check DOL Labor Condition Application disclosure data to see which companies have filed for AI-related roles previously, which is a reliable signal that their HR teams understand OPT documentation requirements.