H-1B Visa AI Intern Jobs
AI Intern roles increasingly appear on H-1B visa petitions under SOC codes like 15-2051 (Data Scientists) and 15-1299 (Computer Occupations). Most sponsors file cap-subject petitions, so timing your offer around the April lottery window is critical. Internships tied to CPT or OPT can bridge you to a full-time H-1B sponsorship pathway.
Find H-1B Visa AI Intern JobsOverview
Showing 5 of 1,179+ AI Intern jobs
See all 1,179+ AI Intern Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Intern roles.
Get Access To All JobsMAIN JOB RESPONSIBILITIES / COMPETENCIES
The Director, Enterprise Artificial Intelligence is responsible for leading the Company's enterprise Artificial Intelligence (AI) strategy and driving business transformation through the adoption of AI-enabled capabilities across the organization. This role partners closely with Executive Leadership, Manufacturing, Supply Chain, Engineering, Quality Assurance, Regulatory Affairs, Commercial Operations, Finance, Human Resources, Cybersecurity, Infrastructure, and Information Technology to identify, prioritize, and implement Artificial Intelligence solutions that improve operational efficiency, decision making, customer experience, innovation, and long-term competitive advantage.
This position provides strategic leadership for enterprise AI governance, Responsible AI, Generative AI, Agentic AI, Machine Learning, Intelligent Automation, and enterprise knowledge management while ensuring AI initiatives deliver measurable business value, align with corporate objectives, and support secure, scalable, and sustainable business transformation.
-
Lead and execute the Company's enterprise Artificial Intelligence strategy aligned with corporate objectives, digital transformation initiatives, and measurable business outcomes.
-
Establish and operationalize an Enterprise AI Center of Excellence (AI CoE) responsible for governance, standards, reusable AI capabilities, and enterprise adoption.
-
Drive enterprise business transformation through the application of Artificial Intelligence, Generative AI, Agentic AI, Machine Learning, Predictive Analytics, and Intelligent Automation.
-
Partner with executive leadership and business stakeholders to identify and prioritize AI initiatives that improve operational efficiency, product quality, customer experience, revenue growth, and employee productivity.
-
Develop enterprise AI roadmaps, investment strategies, business cases, and value realization plans.
-
Establish Responsible AI governance, AI policies, model lifecycle management, and AI risk management practices.
-
Lead implementation of RAG, semantic search, vector databases, AI assistants, and enterprise knowledge management.
-
Integrate AI with Oracle Fusion ERP, OCI, OIC, Salesforce, MES, PLM, enterprise data platforms, and cloud-native applications.
-
Establish KPIs and executive dashboards measuring AI adoption and business value.
-
Lead organizational change management and enterprise AI adoption.
-
Recruit and mentor a team of AI/Business Engineers, Data Engineer/architects and AI Product Owner.
-
Evaluate emerging AI technologies and strategic technology partnerships.
-
Foster innovation, continuous improvement, and responsible AI adoption.
-
Other duties as assigned.
REQUIREMENTS
EDUCATION & TRAINING
- Bachelor’s degree in computer science, Artificial Intelligence, Data Science, Engineering, Information Technology, Business Administration, or related discipline required or equivalent combination of education/experience.
- Advanced degree preferred.
- Professional certifications in AI, Cloud Computing, Enterprise Architecture, Cybersecurity, Project Management, or Data Analytics are highly desirable.
Experience
- 12+ years of progressive leadership experience in enterprise technology, digital transformation, Artificial Intelligence, data analytics, enterprise architecture, software engineering, or related disciplines.
- 3+ years leading enterprise digital AI transformation organizations.
- Demonstrated success developing enterprise AI strategies delivering measurable business transformation.
- Experience with Generative AI, LLMs, Agentic AI, RAG, Machine Learning, Predictive Analytics, and Intelligent Automation.
- Experience in integrating AI with ERP, CRM, Supply Chain, Manufacturing, Finance, HR, and enterprise platforms.
- Experience presenting AI strategies and business outcomes to executive leadership and Boards.
- Enterprise AI governance, organizational change management, and global business transformation.
- FDA-regulated medical devices, biotechnology, pharmaceutical, life sciences, or other regulated industries preferred.
SKILLS
- Strong knowledge of enterprise Artificial Intelligence strategy, governance, operating models, enterprise architecture, and business transformation methodologies, including the development of AI roadmaps, investment strategies, Centers of Excellence, and enterprise adoption frameworks.
- Deep understanding of Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), prompt engineering, AI orchestration frameworks, semantic search, vector databases, AI assistants, autonomous agents, and intelligent automation technologies.
- Strong understanding of Machine Learning, Predictive Analytics, Natural Language Processing (NLP), Computer Vision, AI model lifecycle management, model evaluation, MLOps, LLMOps, and enterprise AI platform operations.
- Strong knowledge of enterprise cloud platforms including Oracle Cloud Infrastructure (OCI), Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), cloud-native architectures, APIs, microservices, enterprise integration, event-driven architectures, and hybrid cloud environments.
- Deep understanding of enterprise data architecture, data governance, master data management, metadata management, data quality, knowledge management, vector storage, and enterprise information management principles supporting AI-enabled decision making.
- Strong understanding of Responsible AI principles, AI governance, cybersecurity, privacy, regulatory compliance, intellectual property protection, model transparency, explainability, AI ethics, enterprise risk management, and secure AI deployment practices.
- Demonstrated ability to align Artificial Intelligence investments with corporate strategy by developing business cases, value realization frameworks, key performance indicators (KPIs), executive dashboards, and measurable financial and operational outcomes.
- Ability to partner effectively with Executive Leadership, Information Technology, Manufacturing, Engineering, Supply Chain, Quality Assurance, Regulatory Affairs, Finance, Human Resources, Cybersecurity, Legal, and external technology partners to deliver enterprise-wide AI capabilities.
- Excellent analytical, strategic planning, organizational, communication, executive presentation, negotiation, financial management, vendor management, stakeholder engagement, and organizational change management skills.
- Demonstrated leadership building, mentoring, and scaling high-performing multidisciplinary teams consisting of AI Engineers, Data Scientists, Machine Learning Engineers, AI Solution Architects, Enterprise Architects, Product Managers, and business technology professionals.
- Proven ability to lead enterprise modernization initiatives, drive innovation, establish AI governance, manage organizational change, and deliver measurable business transformation while maintaining secure, scalable, and responsible AI practices.
Pay range: $200K - $300K - Final compensation/salary will depend on experience.
STAAR Surgical is an Equal Employment Opportunity/Affirmative Action employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran or disability status, or any other characteristic protected by law.
LOCATION
Lake Forest, CA, US
Job Code: 2214
of Openings: 1
MAIN JOB RESPONSIBILITIES / COMPETENCIES
The Director, Enterprise Artificial Intelligence is responsible for leading the Company's enterprise Artificial Intelligence (AI) strategy and driving business transformation through the adoption of AI-enabled capabilities across the organization. This role partners closely with Executive Leadership, Manufacturing, Supply Chain, Engineering, Quality Assurance, Regulatory Affairs, Commercial Operations, Finance, Human Resources, Cybersecurity, Infrastructure, and Information Technology to identify, prioritize, and implement Artificial Intelligence solutions that improve operational efficiency, decision making, customer experience, innovation, and long-term competitive advantage.
This position provides strategic leadership for enterprise AI governance, Responsible AI, Generative AI, Agentic AI, Machine Learning, Intelligent Automation, and enterprise knowledge management while ensuring AI initiatives deliver measurable business value, align with corporate objectives, and support secure, scalable, and sustainable business transformation.
-
Lead and execute the Company's enterprise Artificial Intelligence strategy aligned with corporate objectives, digital transformation initiatives, and measurable business outcomes.
-
Establish and operationalize an Enterprise AI Center of Excellence (AI CoE) responsible for governance, standards, reusable AI capabilities, and enterprise adoption.
-
Drive enterprise business transformation through the application of Artificial Intelligence, Generative AI, Agentic AI, Machine Learning, Predictive Analytics, and Intelligent Automation.
-
Partner with executive leadership and business stakeholders to identify and prioritize AI initiatives that improve operational efficiency, product quality, customer experience, revenue growth, and employee productivity.
-
Develop enterprise AI roadmaps, investment strategies, business cases, and value realization plans.
-
Establish Responsible AI governance, AI policies, model lifecycle management, and AI risk management practices.
-
Lead implementation of RAG, semantic search, vector databases, AI assistants, and enterprise knowledge management.
-
Integrate AI with Oracle Fusion ERP, OCI, OIC, Salesforce, MES, PLM, enterprise data platforms, and cloud-native applications.
-
Establish KPIs and executive dashboards measuring AI adoption and business value.
-
Lead organizational change management and enterprise AI adoption.
-
Recruit and mentor a team of AI/Business Engineers, Data Engineer/architects and AI Product Owner.
-
Evaluate emerging AI technologies and strategic technology partnerships.
-
Foster innovation, continuous improvement, and responsible AI adoption.
-
Other duties as assigned.
REQUIREMENTS
EDUCATION & TRAINING
- Bachelor’s degree in computer science, Artificial Intelligence, Data Science, Engineering, Information Technology, Business Administration, or related discipline required or equivalent combination of education/experience.
- Advanced degree preferred.
- Professional certifications in AI, Cloud Computing, Enterprise Architecture, Cybersecurity, Project Management, or Data Analytics are highly desirable.
Experience
- 12+ years of progressive leadership experience in enterprise technology, digital transformation, Artificial Intelligence, data analytics, enterprise architecture, software engineering, or related disciplines.
- 3+ years leading enterprise digital AI transformation organizations.
- Demonstrated success developing enterprise AI strategies delivering measurable business transformation.
- Experience with Generative AI, LLMs, Agentic AI, RAG, Machine Learning, Predictive Analytics, and Intelligent Automation.
- Experience in integrating AI with ERP, CRM, Supply Chain, Manufacturing, Finance, HR, and enterprise platforms.
- Experience presenting AI strategies and business outcomes to executive leadership and Boards.
- Enterprise AI governance, organizational change management, and global business transformation.
- FDA-regulated medical devices, biotechnology, pharmaceutical, life sciences, or other regulated industries preferred.
SKILLS
- Strong knowledge of enterprise Artificial Intelligence strategy, governance, operating models, enterprise architecture, and business transformation methodologies, including the development of AI roadmaps, investment strategies, Centers of Excellence, and enterprise adoption frameworks.
- Deep understanding of Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), prompt engineering, AI orchestration frameworks, semantic search, vector databases, AI assistants, autonomous agents, and intelligent automation technologies.
- Strong understanding of Machine Learning, Predictive Analytics, Natural Language Processing (NLP), Computer Vision, AI model lifecycle management, model evaluation, MLOps, LLMOps, and enterprise AI platform operations.
- Strong knowledge of enterprise cloud platforms including Oracle Cloud Infrastructure (OCI), Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), cloud-native architectures, APIs, microservices, enterprise integration, event-driven architectures, and hybrid cloud environments.
- Deep understanding of enterprise data architecture, data governance, master data management, metadata management, data quality, knowledge management, vector storage, and enterprise information management principles supporting AI-enabled decision making.
- Strong understanding of Responsible AI principles, AI governance, cybersecurity, privacy, regulatory compliance, intellectual property protection, model transparency, explainability, AI ethics, enterprise risk management, and secure AI deployment practices.
- Demonstrated ability to align Artificial Intelligence investments with corporate strategy by developing business cases, value realization frameworks, key performance indicators (KPIs), executive dashboards, and measurable financial and operational outcomes.
- Ability to partner effectively with Executive Leadership, Information Technology, Manufacturing, Engineering, Supply Chain, Quality Assurance, Regulatory Affairs, Finance, Human Resources, Cybersecurity, Legal, and external technology partners to deliver enterprise-wide AI capabilities.
- Excellent analytical, strategic planning, organizational, communication, executive presentation, negotiation, financial management, vendor management, stakeholder engagement, and organizational change management skills.
- Demonstrated leadership building, mentoring, and scaling high-performing multidisciplinary teams consisting of AI Engineers, Data Scientists, Machine Learning Engineers, AI Solution Architects, Enterprise Architects, Product Managers, and business technology professionals.
- Proven ability to lead enterprise modernization initiatives, drive innovation, establish AI governance, manage organizational change, and deliver measurable business transformation while maintaining secure, scalable, and responsible AI practices.
Pay range: $200K - $300K - Final compensation/salary will depend on experience.
STAAR Surgical is an Equal Employment Opportunity/Affirmative Action employer and all qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran or disability status, or any other characteristic protected by law.
LOCATION
Lake Forest, CA, US
Job Code: 2214
of Openings: 1
See all 1,179+ H-1B Visa AI Intern Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa AI Intern Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an AI Intern
Match your degree to the SOC code
USCIS requires a direct relationship between your degree field and the AI Intern role. A computer science or data science degree maps cleanly, but a business or economics degree may trigger an RFE unless the job description specifies technical coursework requirements.
Target employers with E-Verify enrollment
If you're on STEM OPT bridging to H-1B, your employer must be enrolled in E-Verify. Confirm enrollment before accepting an offer, not after signing, since switching employers mid-OPT restarts the verification clock.
Search LCA-verified AI sponsors on Migrate Mate
Pull up AI and machine learning roles on Migrate Mate to see which employers have filed Labor Condition Applications for this occupation. That DOL filing history tells you which companies have actually moved through the H-1B process, not just listed sponsorship as possible.
Check prevailing wage before negotiating your offer
Your employer's LCA must certify your wage at or above the DOL prevailing wage for the role's SOC code and location. Run the OFLC Wage Search before salary negotiations so you know the floor and can flag any offer that would create a filing problem.
Clarify cap-exempt status for university-affiliated roles
AI internships hosted at nonprofits affiliated with universities or at government research institutions may qualify as cap-exempt, bypassing the annual lottery. Ask directly whether the petitioning employer qualifies under INA 214(g)(5)(A) before assuming you'll need to wait for an April registration window.
Get the I-129 petition timeline in writing before you start
For intern-to-full-time conversions, confirm your employer plans to file the I-129 by April 1 for an October 1 start. A delayed filing can leave a gap between your OPT expiration and H-1B activation, even if USCIS approves the petition.
H-1B Visa AI Intern: Frequently Asked Questions
Can an internship qualify for H-1B sponsorship?
Yes, if the internship meets the specialty occupation standard, meaning the role normally requires at least a bachelor's degree in a directly related field. AI internships involving model development, data engineering, or research often qualify under computer occupations SOC codes. The employer must be willing to file an LCA with DOL and an I-129 petition with USCIS, which many larger tech and research employers do for competitive intern talent.
How do I find AI Intern employers who actually sponsor H-1B visas?
Search AI Intern roles on Migrate Mate, which surfaces employers based on verified DOL Labor Condition Application filing history. LCA filings are the clearest signal that a company has completed the H-1B sponsorship process, not just listed it as a possibility. Filtering by LCA history removes employers who say they sponsor but have no documented filings for this occupation.
Does working as an AI Intern on OPT count toward H-1B specialty occupation experience?
Yes, OPT work in an AI or data science role is treated as qualifying U.S. work experience when USCIS evaluates your H-1B petition. It strengthens the specialty occupation argument, particularly if the OPT employer is the same as the H-1B petitioner. Document your OPT role with an offer letter, pay stubs, and a detailed job description matching the technical requirements in your degree field.
What happens if I'm on STEM OPT and my AI Intern role ends before H-1B selection?
You can continue working for a different E-Verify-enrolled employer in a role related to your STEM degree without restarting your 24-month STEM OPT extension, as long as you update your SEVIS record through your DSO within five days of the job change. If no qualifying role is available, you enter a 60-day unemployment grace period. Staying within that window while pursuing new AI roles is manageable, but you'll need a new employer to file your H-1B petition in the next April registration cycle.
Do AI Intern H-1B petitions face higher RFE rates than full-time roles?
Internships can draw additional USCIS scrutiny because officers sometimes question whether a temporary role genuinely requires a degree-level specialist. The strongest defense is a detailed job description tying specific AI tasks, such as training production models or building data pipelines, to coursework in computer science or statistics. An employer with a documented track record of H-1B approvals for similar intern roles also reduces RFE risk significantly.