AI Data Specialist Jobs in USA with Visa Sponsorship
AI Data Specialists are among the most actively sponsored roles in the U.S. right now. Most positions qualify under H-1B visa specialty occupation rules, and employers across tech, finance, and healthcare regularly file LCAs for this title. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsGENERAL INFORMATION
Req #
WD00108341
Career area:
Hardware Engineering
Country/Region:
United States of America
State:
North Carolina
City:
Morrisville
Date:
Thursday, November 5, 2026
Working time:
Full-time
ADDITIONAL LOCATIONS:
* United States of America - North Carolina - Morrisville
WHY WORK AT LENOVO
We are Lenovo. We do what we say. We own what we do. We WOW our customers.
Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.
DESCRIPTION AND REQUIREMENTS
Job Summary: As an AI Data Specialist, you will play a key role in the design, development, and deployment of an Agentic AI platform that streamlines the creation of AI-driven customer solutions. You will work closely with AI engineers and cross-functional teams to support the deployment, integration, and scaling of AI services across enterprise environments. In this role, you will leverage your expertise in data management, AI technologies, and development practices to build efficient, reusable, and scalable data-driven solutions. You will be responsible for ensuring that data pipelines, models, and AI components are effectively integrated into a cohesive and high-performing platform. To succeed, you should possess a strong understanding of AI and data ecosystems, demonstrate hands-on technical skills, and have the ability to transform complex data and AI tools into standardized, repeatable solutions that drive business value.
This is a remote role based in the US. Please see below for important information regarding the recruiting process for fully remote roles.
Job Responsibilities
AI Solution Development:
- Design and deploy AI solutions using LLMs, SLMs, VLMs, and Agentic AI frameworks.
- Support AI architecture, solution design, and proof-of-concept initiatives.
Data Engineering & RAG:
- Build scalable data pipelines for ingestion, transformation, and enrichment.
- Develop RAG solutions using vector databases such as Milvus and PGVector.
AI Platform & Integration:
- Integrate AI services, APIs, and microservices into enterprise platforms.
- Optimize model training and inference using GPU-accelerated technologies.
MLOps & Operations:
- Implement MLOps, LLMOps, and pipeline orchestration best practices.
- Monitor, optimize, and maintain AI workflows and platform performance.
Security & Documentation:
- Ensure data security, governance, and compliance requirements are met.
- Create technical documentation and maintain high-quality, reusable code.
Collaboration & Innovation:
- Partner with cross-functional teams to deliver scalable AI solutions.
- Evaluate and adopt emerging AI and data technologies to improve platform capabilities.
BASIC QUALIFICATIONS
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field.
- 5+ years of experience in AI/data engineering and implementation roles, including data engineering, machine learning, NLP, or Generative AI-focused data solutions.
- 2+ years of hands-on experience in building end-to-end Generative AI and data-driven solutions, including data preprocessing, embedding generation, and Retrieval-Augmented Generation (RAG) pipelines using LLMs and multimodal models (e.g., OpenAI, Anthropic, Llama, Hugging Face, Amazon Bedrock).
PREFERRED QUALIFICATIONS
- Strong experience with data processing frameworks and pipeline development.
- Hands-on experience with vector databases such as Milvus, PostgreSQL (PGVector), Pinecone, or similar, including embedding management and semantic search implementations.
- Experience working with the NVIDIA AI ecosystem (e.g., GPUs, CUDA, TensorRT, NeMo) or equivalent acceleration technologies for efficient data processing, model training, and inference is a strong plus.
- Strong understanding of data architectures involving structured, semi-structured, and unstructured data, and building scalable pipelines to support AI/ML workloads.
- Experience integrating AI/data solutions across cloud and on-premise environments, including containerization and orchestration using Docker and Kubernetes.
- Proven experience implementing MLOps, LLMOps, and DataOps practices, including CI/CD pipelines, data versioning, monitoring, and lifecycle management using tools such as Jenkins, GitLab, MLflow, or similar.
- Strong programming skills in Python, with experience in data processing libraries (e.g., Pandas, PySpark), and familiarity with API development.
- Solid understanding of data governance, security, and compliance, including handling sensitive data and implementing access controls and encryption.
- Strong problem-solving skills and ability to translate complex data and AI requirements into scalable, reusable solutions.
THE INTERVIEW PROCESS
What to expect during your interview: Our virtual interviews including phone screens are conducted on camera to support an engaging and consistent interview experience. Please ensure you have access to a camera, audio, and reliable internet connectivity. If you are unable to participate on camera, please let your recruiter know in advance.
Candidates who progress to the final stage of the selection process for fully remote roles will be invited to complete their final interview in person to learn more about Lenovo, meet key stakeholders, and experience our workplace and culture firsthand.
Remote
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.
ADDITIONAL LOCATIONS:
* United States of America - North Carolina - Morrisville
* United States of America
* United States of America - North Carolina
* United States of America - North Carolina - Morrisville
PAY TRANSPARENCY
The anticipated annual compensation range for this position is 120,600–184,920 USD. Final compensation will be based on relevant experience, skills, and business considerations. Individuals may also be considered for bonuses and/or commissions. Lenovo’s various benefits can be found at www.lenovobenefits.com.
In compliance with Colorado’s Equal Pay for Equal Work Act (EPEWA), the expected application deadline for this position is 11-26-2026. This requirement applies to both internal and external candidates.
GENERAL INFORMATION
Req #
WD00108341
Career area:
Hardware Engineering
Country/Region:
United States of America
State:
North Carolina
City:
Morrisville
Date:
Thursday, November 5, 2026
Working time:
Full-time
ADDITIONAL LOCATIONS:
* United States of America - North Carolina - Morrisville
WHY WORK AT LENOVO
We are Lenovo. We do what we say. We own what we do. We WOW our customers.
Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.
DESCRIPTION AND REQUIREMENTS
Job Summary: As an AI Data Specialist, you will play a key role in the design, development, and deployment of an Agentic AI platform that streamlines the creation of AI-driven customer solutions. You will work closely with AI engineers and cross-functional teams to support the deployment, integration, and scaling of AI services across enterprise environments. In this role, you will leverage your expertise in data management, AI technologies, and development practices to build efficient, reusable, and scalable data-driven solutions. You will be responsible for ensuring that data pipelines, models, and AI components are effectively integrated into a cohesive and high-performing platform. To succeed, you should possess a strong understanding of AI and data ecosystems, demonstrate hands-on technical skills, and have the ability to transform complex data and AI tools into standardized, repeatable solutions that drive business value.
This is a remote role based in the US. Please see below for important information regarding the recruiting process for fully remote roles.
Job Responsibilities
AI Solution Development:
- Design and deploy AI solutions using LLMs, SLMs, VLMs, and Agentic AI frameworks.
- Support AI architecture, solution design, and proof-of-concept initiatives.
Data Engineering & RAG:
- Build scalable data pipelines for ingestion, transformation, and enrichment.
- Develop RAG solutions using vector databases such as Milvus and PGVector.
AI Platform & Integration:
- Integrate AI services, APIs, and microservices into enterprise platforms.
- Optimize model training and inference using GPU-accelerated technologies.
MLOps & Operations:
- Implement MLOps, LLMOps, and pipeline orchestration best practices.
- Monitor, optimize, and maintain AI workflows and platform performance.
Security & Documentation:
- Ensure data security, governance, and compliance requirements are met.
- Create technical documentation and maintain high-quality, reusable code.
Collaboration & Innovation:
- Partner with cross-functional teams to deliver scalable AI solutions.
- Evaluate and adopt emerging AI and data technologies to improve platform capabilities.
BASIC QUALIFICATIONS
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field.
- 5+ years of experience in AI/data engineering and implementation roles, including data engineering, machine learning, NLP, or Generative AI-focused data solutions.
- 2+ years of hands-on experience in building end-to-end Generative AI and data-driven solutions, including data preprocessing, embedding generation, and Retrieval-Augmented Generation (RAG) pipelines using LLMs and multimodal models (e.g., OpenAI, Anthropic, Llama, Hugging Face, Amazon Bedrock).
PREFERRED QUALIFICATIONS
- Strong experience with data processing frameworks and pipeline development.
- Hands-on experience with vector databases such as Milvus, PostgreSQL (PGVector), Pinecone, or similar, including embedding management and semantic search implementations.
- Experience working with the NVIDIA AI ecosystem (e.g., GPUs, CUDA, TensorRT, NeMo) or equivalent acceleration technologies for efficient data processing, model training, and inference is a strong plus.
- Strong understanding of data architectures involving structured, semi-structured, and unstructured data, and building scalable pipelines to support AI/ML workloads.
- Experience integrating AI/data solutions across cloud and on-premise environments, including containerization and orchestration using Docker and Kubernetes.
- Proven experience implementing MLOps, LLMOps, and DataOps practices, including CI/CD pipelines, data versioning, monitoring, and lifecycle management using tools such as Jenkins, GitLab, MLflow, or similar.
- Strong programming skills in Python, with experience in data processing libraries (e.g., Pandas, PySpark), and familiarity with API development.
- Solid understanding of data governance, security, and compliance, including handling sensitive data and implementing access controls and encryption.
- Strong problem-solving skills and ability to translate complex data and AI requirements into scalable, reusable solutions.
THE INTERVIEW PROCESS
What to expect during your interview: Our virtual interviews including phone screens are conducted on camera to support an engaging and consistent interview experience. Please ensure you have access to a camera, audio, and reliable internet connectivity. If you are unable to participate on camera, please let your recruiter know in advance.
Candidates who progress to the final stage of the selection process for fully remote roles will be invited to complete their final interview in person to learn more about Lenovo, meet key stakeholders, and experience our workplace and culture firsthand.
Remote
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.
ADDITIONAL LOCATIONS:
* United States of America - North Carolina - Morrisville
* United States of America
* United States of America - North Carolina
* United States of America - North Carolina - Morrisville
PAY TRANSPARENCY
The anticipated annual compensation range for this position is 120,600–184,920 USD. Final compensation will be based on relevant experience, skills, and business considerations. Individuals may also be considered for bonuses and/or commissions. Lenovo’s various benefits can be found at www.lenovobenefits.com.
In compliance with Colorado’s Equal Pay for Equal Work Act (EPEWA), the expected application deadline for this position is 11-26-2026. This requirement applies to both internal and external candidates.
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Sign up for free to unlock all listings, filter by visa type, and get alerts for new AI Data Specialist roles.
Get Access To All JobsTips for Finding Visa Sponsorship as an AI Data Specialist
Lead with your degree field, not just your degree
Employers filing an H-1B for this role need to show the position requires a specific degree. A background in computer science, statistics, or data science strengthens the specialty occupation argument more than a general STEM degree.
Highlight experience with AI frameworks in your resume
Concrete tools matter for LCA job descriptions. Listing experience with PyTorch, TensorFlow, or large language model pipelines gives employers the specificity they need to write a defensible H-1B job description to submit to USCIS.
Target employers with active LCA filings in AI and data
Not all companies sponsor. Focus on employers with a documented history of filing Labor Condition Applications for data and AI roles. These companies already understand the process and are far less likely to rescind offers over sponsorship complexity.
Understand the difference between OPT and H-1B timing
If you're on F-1 OPT or STEM OPT extension, your employer needs to file your H-1B cap petition by April 1 for an October 1 start. Missing this window means reapplying next year, so raise the timeline early in negotiations.
Use your project portfolio to justify specialty occupation
USCIS scrutinizes AI and data roles more than traditional software engineering positions. A portfolio showing model development, data pipeline architecture, or research contributions helps demonstrate that the role genuinely requires specialized theoretical knowledge.
Frequently Asked Questions
Does an AI Data Specialist role qualify as an H-1B specialty occupation?
Yes, in most cases. USCIS requires the position to normally require at least a bachelor's degree in a specific specialty. AI Data Specialist roles tied to computer science, statistics, or data science typically satisfy this. The risk arises when a job description is written broadly enough that any STEM degree could qualify, which weakens the specialty occupation argument. Employers and attorneys often tighten job descriptions before filing to reduce this exposure.
What degree do I need for an employer to sponsor me as an AI Data Specialist?
A bachelor's degree or higher in computer science, data science, statistics, mathematics, or a closely related field is the standard requirement. The degree must relate directly to the duties of the role. If your degree is in a tangentially related field, a combination of education and progressive work experience can sometimes substitute, but this requires stronger documentation and is harder to defend at USCIS.
How do I find AI Data Specialist jobs that offer visa sponsorship?
The most efficient approach is to use a platform that filters specifically for sponsorship-willing employers. Migrate Mate is built for exactly this, with AI and data roles sourced from companies that actively file H-1B visa petitions. Browsing general job boards and filtering manually is significantly slower and often surfaces roles where sponsorship is listed as possible but never confirmed by the employer.
Are H-1B approvals common for AI and data roles, or is there high denial risk?
Approval rates for AI and data roles are generally strong when the job description is well-constructed and the applicant's degree aligns with the position. Denials most often occur when USCIS issues a Request for Evidence questioning whether the role truly requires a specialized degree, or when the employer's job description is too generic. Companies with experienced immigration counsel file better petitions and have lower RFE rates for these roles.
Can I switch employers after my H-1B is approved for an AI Data Specialist position?
Yes. H-1B portability allows you to transfer your visa to a new employer once your current petition has been approved and you've entered valid H-1B status. The new employer must file an H-1B transfer petition before your start date with them. You can begin working for the new employer as soon as the transfer petition is filed and receipt is confirmed, without waiting for full approval.
What is the prevailing wage requirement for sponsored AI Data Specialist jobs?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.