STEM OPT AI ML Platform Jobs
AI ML Platform roles sit squarely within STEM OPT eligibility, supported by computer science, data science, and engineering degrees. Your initial 12-month OPT extends by 24 months once your employer enrolls in E-Verify and files your I-983 training plan, giving you up to 36 months to build a career in machine learning infrastructure.
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INTRODUCTION
Join Apple Services Engineering to build the next generation of AI evaluation systems. We are seeking machine learning platform engineers at multiple levels (Mid-Level to Principal) to architect and build high-availability services and internal tools that enable self-service evaluation at scale. You will partner with researchers to operationalize their innovations, transforming complex workflows into intuitive, developer-first platforms. We are looking for builders who thrive in the ambiguity of new initiatives and are passionate about creating scalable infrastructure.
DESCRIPTION
You will join the engineering team responsible for democratizing AI evaluation across the organization. Your focus will be on developing the developer experience—architecting and implementing the APIs, SDKs, and platform services that turn complex evaluation metrics into simple, self-service calls. You will work hand-in-hand with researchers to operationalize sophisticated measurement techniques, ensuring they scale reliably within our high-availability infrastructure. In this role, you will drive the engineering standards for a new organization, upholding the code quality, automation, and testing rigor required to support the rapid evolution of Generative AI and Agentic systems.
Responsibilities
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System Design & Implementation: Design, code, and ship high-quality Python services. For senior candidates: Lead the architecture for the core evaluation engine and distributed services. For mid-level candidates: Own the end-to-end implementation of specific features and API endpoints.
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Technical Leadership & Collaboration: Mentor junior engineers, conduct code reviews, and drive technical decision-making. Foster a culture of technical excellence and rapid delivery through example and collaboration.
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Operationalizing Science: Partner closely with Applied Scientists to translate novel metrics, judge prompts, and scoring algorithms into scalable, production-grade services. Create frameworks to evaluate not just simple responses, but also multi-turn agent trajectories and tool usage.
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System Integration: Serve as a technical bridge between the research organization and the broader engineering ecosystem, ensuring our tools integrate seamlessly with existing ML infrastructure and developer workflows.
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Engineering Rigor: Champion the software development lifecycle (SDLC) for the team, writing comprehensive automated testing (CI/CD), and instrumenting monitoring to ensure high availability and reliability.
MINIMUM QUALIFICATIONS
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2+ years of hands-on software engineering experience (or Master's degree with relevant project experience). Note: We are hiring across multiple seniority levels; expectations will scale with experience.
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Strong proficiency in the Python ecosystem (e.g., FastAPI, Pydantic, Pandas). You are capable of writing production-grade code and contributing to architectural discussions on day one.
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Customer Obsession & Product Thinking: Experience acting as a technical partner to internal customers. You can translate vague requirements from other teams into concrete engineering specifications.
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Demonstrated experience partnering with Data Scientists or Researchers: You have the ability to navigate the ambiguity of research workflows and operationalize scientific code.
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Functional literacy in AI/ML concepts: You understand the fundamental lifecycle of machine learning (datasets, training vs. inference, evaluation metrics) and can discuss the engineering challenges involved in serving models.
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Strong expertise in API Design & Internal Tools: You have built APIs that other developers rely on, with a focus on versioning, backward compatibility, and developer experience.
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Operational excellence background: You have practical experience using CI/CD pipelines, containerization (Docker/Kubernetes), and monitoring (Datadog/Prometheus).
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BS CS, Master's preferred.
PREFERRED QUALIFICATIONS
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Experience building MLOps & Platform Infrastructure: You have architected the foundational infrastructure for AI, such as model registries, inference services, or feature stores (using tools like Kubernetes, Ray, or Kubeflow).
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Deep familiarity with AI Evaluation Frameworks: You have used or contributed to modern evaluation tools like DeepEval, Ragas, TruLens, or LangSmith. You understand how to implement and scale model-based evaluation workflows.
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Deep understanding of Generative AI & Agents: You understand the engineering challenges of relying on LLMs and Agents as software components—specifically managing token economics, handling rate limits, and evaluating non-deterministic, multi-step reasoning capabilities.
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Builder Experience: You have thrived in startup-like environments, navigating high ambiguity to deliver complex technical roadmaps from scratch.
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 $171,600 and $258,100, 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.
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Get Access To All JobsTips for Finding STEM OPT Authorization in AI ML Platform
Verify your CIP code before applying
Check that your degree's Classification of Instructional Programs code maps to a STEM-designated field. AI and ML Platform roles most often qualify under CIP codes for computer science, electrical engineering, or applied mathematics. Your DSO can confirm your I-20 reflects the right code.
Check E-Verify status before accepting offers
STEM OPT requires your employer to be enrolled in E-Verify before your extension starts. Search the E-Verify employer search tool by company name to confirm active participation. A company that isn't enrolled can't legally employ you on a STEM OPT extension.
Target platform teams at E-Verify enrolled companies
ML platform and MLOps roles are concentrated at companies running large-scale model infrastructure. Use Migrate Mate to filter AI ML Platform jobs specifically to E-Verify enrolled employers, so you're only applying to companies that can legally support your STEM OPT extension.
Align your I-983 training plan to ML platform work
Your I-983 must connect your STEM degree to your day-to-day platform work. Frame objectives around specific skills like distributed training infrastructure, model deployment pipelines, or feature store architecture. Vague plans get flagged by DSOs and can delay your extension start date.
Use O*NET to anchor your specialty occupation case
Pull the O*NET occupation profile for your target role before you negotiate your offer. ML platform engineers typically fall under Software Developers or Computer and Information Research Scientists, both of which require a bachelor's degree in a specific technical field, which strengthens your OPT-to-H-1B visa transition argument.
File your STEM OPT extension at least 90 days early
USCIS recommends submitting your I-765 extension application up to 90 days before your initial OPT ends. Late filing eliminates the 180-day automatic extension that keeps you authorized while your application is pending. Confirm your exact deadline with your DSO as soon as you accept an offer.
Frequently Asked Questions
Does my STEM degree qualify me for the 24-month STEM OPT extension in an AI ML Platform role?
It depends on your specific degree's CIP code, not just the subject area. Degrees in computer science, electrical engineering, applied mathematics, statistics, and data science are commonly STEM-designated and qualify for the extension. Your DSO confirms eligibility by checking whether your I-20 reflects a CIP code on the STEM Designated Degree Program List published by the Department of Homeland Security. An AI ML Platform role itself doesn't confer eligibility; your degree does.
What E-Verify requirement applies to my employer for STEM OPT?
Your employer must be actively enrolled in E-Verify before your STEM OPT extension begins, not just at the time you accept an offer. Enrollment is required at the specific worksite where you'll be employed. You can verify enrollment using the E-Verify employer search tool before signing anything. If your employer is acquired or restructures after your extension starts, the new legal entity must independently enroll in E-Verify.
What should my I-983 training plan include for an AI ML Platform role?
Your I-983 must describe how the practical training directly relates to your STEM degree and supports your professional development goals. For AI ML Platform roles, this typically means documenting objectives around model deployment systems, data pipeline architecture, distributed computing, or ML infrastructure reliability. Your employer's authorized representative signs the form, and your DSO must receive it before your extension is authorized. Generic job descriptions without degree-field connections are commonly flagged.
How does cap-gap protection work if my H-1B is selected while I'm on STEM OPT?
If your employer files an H-1B petition on your behalf before your STEM OPT expires and USCIS selects it in the lottery, cap-gap automatically extends your OPT work authorization through September 30 of that year. Your EAD remains valid during this period even if it has expired on its face. USCIS issues a cap-gap extension automatically; no separate application is required. Your DSO can issue an updated I-20 reflecting the cap-gap period.
Where can I find AI ML Platform jobs that are open to STEM OPT candidates?
Use Migrate Mate to search AI ML Platform jobs filtered to employers enrolled in E-Verify, which is the baseline requirement for hiring STEM OPT students. Many job listings don't explicitly state E-Verify enrollment, so filtering by confirmed enrollment saves significant time. Migrate Mate surfaces roles where the employer infrastructure already supports F-1 STEM OPT work authorization, reducing the risk of accepting an offer from a company that can't legally extend your status.