OPT AI Data Specialist Jobs
AI Data Specialist roles involve labeling, curating, and evaluating datasets that train machine learning models, making them a strong fit for F-1 OPT students with backgrounds in computer science, data science, or linguistics. Many employers in this space have experience working with international candidates on STEM OPT, which covers the full 36-month authorization period.
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BeaconFire is based in Central NJ, specializing in Software Development, Web Development, and Business Intelligence; looking for a strong agentic AI developer who can build and productionize Vertex AI–based RAG systems (Vertex AI Search / Vertex AI RAG patterns), design reliable tool-using agents, and work comfortably with vector databases and graph databases.
About the Role
You’ll own end-to-end delivery: ingestion, retrieval, agent orchestration, evaluation, and deployment.
Responsibilities
- Collaborate with the team to design and develop high quality Web applications using Python, Flask, Django, and related technologies.
- Write clean and efficient code, and ensure code maintainability and reusability.
- Design and implement RAG pipelines on Google Cloud / Vertex AI (chunking, embeddings, indexing, retrieval, reranking, grounding).
- Build agentic workflows (tool use, planning, reflection/guardrails, structured outputs) using Python-first frameworks.
- Perform code reviews to ensure code quality and consistency.
- Conduct testing to ensure application quality and reliability.
- Create and maintain technical documentation for web applications.
- Participate in project planning, estimation, and prioritization.
- Stay up to date with the latest technologies for Python development.
- Define and run evaluation (retrieval metrics, answer quality, hallucination/grounding checks), and improve system quality iteratively.
- Ship to production: APIs, monitoring/observability, cost/performance optimization, CI/CD, and security best practices.
Qualifications
- Experience in software development in Python3.
- Decent understanding of the software development/testing life cycle.
- Knowledge of relational databases (e.g. MySQL, PostgreSQL, etc).
- Experience with version control tools, such as Git.
- Experience building RAG solutions (hybrid search, reranking, chunking strategies, embeddings, prompt + schema design).
- Familiar with at least one agentic framework (e.g., LangGraph/LangChain, LlamaIndex, Semantic Kernel, AutoGen) and tool/function calling patterns.
- Solid knowledge of vector search concepts and at least one vector DB in production.
- Strong engineering practices: code reviews, testing, telemetry, secure-by-design, reliability mindset.
Preferred Skills
- Master’s Degree in Computer Science, Software Engineering, or related field.
- 1+ year professional experience in Python web application development with either Flask or Django.
- Experience in RESTful API development in Python.
- Understanding of Python web application frameworks such as Flask or Django.
- Experience with Cloud services, such as AWS.
- Experience with Vertex AI and GCP fundamentals (IAM, logging/monitoring, CloudRun/GKE, storage).
- Knowledge graphs for RAG (entity linking, graph traversal + retrieval fusion).
- Streaming/messaging (Pub/Sub, Kafka), document pipelines (Document AI), and multilingual retrieval.
- Experience with evaluation tooling (RAGAS, TruLens, custom eval harnesses), prompt/version management.
- Frontend integration (basic React/Next.js) or platform enablement (internal developer tooling).
Pay range and compensation package
BeaconFire is an E-verified company and provides equal employment opportunities (visa sponsorship provided).
Equal Opportunity Statement
BeaconFire is committed to diversity and inclusivity.
About the Company
BeaconFire is based in Central NJ, specializing in Software Development, Web Development, and Business Intelligence; looking for a strong agentic AI developer who can build and productionize Vertex AI–based RAG systems (Vertex AI Search / Vertex AI RAG patterns), design reliable tool-using agents, and work comfortably with vector databases and graph databases.
About the Role
You’ll own end-to-end delivery: ingestion, retrieval, agent orchestration, evaluation, and deployment.
Responsibilities
- Collaborate with the team to design and develop high quality Web applications using Python, Flask, Django, and related technologies.
- Write clean and efficient code, and ensure code maintainability and reusability.
- Design and implement RAG pipelines on Google Cloud / Vertex AI (chunking, embeddings, indexing, retrieval, reranking, grounding).
- Build agentic workflows (tool use, planning, reflection/guardrails, structured outputs) using Python-first frameworks.
- Perform code reviews to ensure code quality and consistency.
- Conduct testing to ensure application quality and reliability.
- Create and maintain technical documentation for web applications.
- Participate in project planning, estimation, and prioritization.
- Stay up to date with the latest technologies for Python development.
- Define and run evaluation (retrieval metrics, answer quality, hallucination/grounding checks), and improve system quality iteratively.
- Ship to production: APIs, monitoring/observability, cost/performance optimization, CI/CD, and security best practices.
Qualifications
- Experience in software development in Python3.
- Decent understanding of the software development/testing life cycle.
- Knowledge of relational databases (e.g. MySQL, PostgreSQL, etc).
- Experience with version control tools, such as Git.
- Experience building RAG solutions (hybrid search, reranking, chunking strategies, embeddings, prompt + schema design).
- Familiar with at least one agentic framework (e.g., LangGraph/LangChain, LlamaIndex, Semantic Kernel, AutoGen) and tool/function calling patterns.
- Solid knowledge of vector search concepts and at least one vector DB in production.
- Strong engineering practices: code reviews, testing, telemetry, secure-by-design, reliability mindset.
Preferred Skills
- Master’s Degree in Computer Science, Software Engineering, or related field.
- 1+ year professional experience in Python web application development with either Flask or Django.
- Experience in RESTful API development in Python.
- Understanding of Python web application frameworks such as Flask or Django.
- Experience with Cloud services, such as AWS.
- Experience with Vertex AI and GCP fundamentals (IAM, logging/monitoring, CloudRun/GKE, storage).
- Knowledge graphs for RAG (entity linking, graph traversal + retrieval fusion).
- Streaming/messaging (Pub/Sub, Kafka), document pipelines (Document AI), and multilingual retrieval.
- Experience with evaluation tooling (RAGAS, TruLens, custom eval harnesses), prompt/version management.
- Frontend integration (basic React/Next.js) or platform enablement (internal developer tooling).
Pay range and compensation package
BeaconFire is an E-verified company and provides equal employment opportunities (visa sponsorship provided).
Equal Opportunity Statement
BeaconFire is committed to diversity and inclusivity.
See all 352+ OPT AI Data Specialist Jobs
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Get Access To All JobsTips for Finding OPT Sponsorship as an AI Data Specialist
Lead with your STEM OPT timeline upfront
Mention your 36-month STEM OPT authorization early in applications and interviews. Many hiring managers don't distinguish between standard and STEM OPT, so clarifying the timeline removes the biggest objection before it becomes one.
Target companies with active AI research pipelines
AI labs, autonomous vehicle companies, and enterprise software firms run continuous data annotation and evaluation cycles. These organizations hire OPT candidates more regularly because data work scales with headcount, not visa lottery timing.
Highlight domain-specific annotation experience
If you've labeled medical imaging, multilingual text, or audio datasets, call that out specifically. Domain expertise makes you harder to replace and signals to employers that sponsoring you after OPT is worth the investment.
Show familiarity with data quality frameworks
Employers want candidates who understand inter-annotator agreement, schema design, and quality control pipelines, not just labeling tools. Framing your experience around data quality positions you for senior roles that are more likely to sponsor.
Connect your degree field to the role directly
STEM OPT eligibility depends on your degree field. Linguistics, statistics, computer science, and cognitive science all qualify. Make that connection explicit on your resume so hiring managers and HR teams don't question your authorization status.
Apply before your OPT clock runs low
Employers are more comfortable starting H-1B visa or other sponsorship conversations with 18 or more months remaining on your OPT. Starting your job search early gives you negotiating room and time to find a company willing to sponsor.
AI Data Specialist OPT: Frequently Asked Questions
Do AI Data Specialist roles qualify for STEM OPT extension?
Yes, in most cases. AI Data Specialist positions typically fall under computer science, data science, or information technology degree classifications, all of which are on the STEM Designated Degree Program list. Your degree field, not the job title, determines eligibility, so confirm your CIP code with your DSO before applying.
How do I find AI Data Specialist jobs that are open to OPT candidates?
Migrate Mate filters job listings specifically for visa sponsorship openness, so you're not wasting applications on employers who won't consider international candidates. Searching there saves significant time compared to filtering through general listings and cold-emailing recruiters to ask about sponsorship policies.
Will I need H-1B sponsorship to stay in this role long-term?
For most full-time positions, yes. After STEM OPT ends, H-1B is the most common next step, though some AI data roles at qualifying nonprofits or universities may be cap-exempt. Start sponsorship conversations with your employer at least 12 months before your OPT expires to give adequate time for H-1B preparation.
Can I work as a contractor or on a 1099 basis as an AI Data Specialist on OPT?
OPT requires that your employment be directly related to your degree field, but self-employment and independent contracting are permitted as long as you're working for yourself, not classified as an employee of a single client. If a company wants to hire you as a contractor through their own payroll vendor, that typically qualifies. Consult your DSO to confirm any arrangement.
What should I include on my resume to pass OPT employer screening for this role?
List your visa status, OPT end date, and STEM extension eligibility clearly in a summary or header section. For AI Data Specialist roles specifically, include annotation tools you've used, dataset types you've worked with, and any quality assurance or inter-annotator agreement experience. Employers in AI move quickly and want to assess authorization at a glance.