STEM OPT AI Data Specialist Jobs
AI Data Specialist roles in machine learning, data labeling, and AI pipeline management qualify for STEM OPT because they sit under STEM-designated CIP codes in computer science and data science. Your employer must be enrolled in E-Verify, and your 24-month STEM OPT extension gives you up to 36 months total to build experience in this field.
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Get Access To All JobsGENERAL INFORMATION
Req #
WD00099074
Career area:
Artificial Intelligence
Country/Region:
United States of America
State:
North Carolina
City:
Morrisville
Date:
Wednesday, May 27, 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 #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Guided by its vision of “Smarter Technology for All”, Lenovo is executing a Hybrid AI strategy that spans Personal AI – one personal AI, multiple devices; and Enterprise AI – helping customers turn data into insights and value. This strategy is delivered through the Group’s commitment to world-class innovation and a full-stack AI portfolio, including devices (PCs, workstations, smartphones, tablets, accessories), infrastructure solutions (server, storage, edge, high performance computing and software defined infrastructure), as well as software, solutions, and services. With a global footprint spanning 21 research and development locations in 11 markets, and a global supply chain including more than 30 manufacturing sites across 10 markets, Lenovo is widely recognized for its operational excellence, including ranking #8 in the Gartner Supply Chain Top 25. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
DESCRIPTION AND REQUIREMENTS
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 role sits within Lenovo’s Solutions & Services Group (SSG), the global organization that brings together our end-to-end AI solutions and services to turn customer vision into value. You’ll be joining a new, distributed engineering team building the xIQ Agent Platform, an AI-native delivery platform that powers Lenovo’s Agentic AI strategy across hybrid cloud, on-prem, and edge.
- Design, develop, and implement data-driven AI solutions for an Agentic AI platform, aligning with enterprise architecture and business objectives.
- Build and maintain scalable data processing pipelines for AI workloads, including data ingestion, cleansing, transformation, and feature engineering.
- Develop and deploy end-to-end AI systems using LLMs, SLMs, and VLMs for advanced data processing, enrichment, and automation.
- Leverage NVIDIA AI technologies (e.g., CUDA, NV-Ingest, VLM..etc) or similar platforms to optimize model training, fine-tuning, and inference performance.
- Implement and manage vector databases such as Milvus, PostgreSQL (PGVector), or other vector stores to support semantic search, embeddings, and Retrieval-Augmented Generation (RAG) use cases.
- Design and optimize data and retrieval pipelines that integrate structured and unstructured data with LLM-based reasoning systems.
- Develop and integrate AI components (APIs, microservices, inference layers) into enterprise platforms across cloud, on-premise, and edge environments.
- Select and implement data engineering and pipeline orchestration tools to ensure scalable and reliable data workflows.
- Apply best practices in data engineering, MLOps, and AIOps, including pipeline monitoring, versioning, and performance tuning.
- Ensure data security, governance, and compliance, including encryption, access control, and secure data handling practices.
- Write clean, maintainable, and reusable code following enterprise development standards and best practices.
- Create detailed technical documentation, including data flow architectures, pipeline designs, model integration patterns, and system interfaces.
- Continuously evaluate and adopt emerging AI, LLM, and data technologies to improve solution effectiveness and scalability.
- Support solution design discussions, PoCs, and pre-sales activities by providing expertise in AI data architecture and implementation.
- Effectively communicate technical designs, data strategies, and AI solutions to both technical teams and business stakeholders.
BASIC QUALIFICATIONS:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field.
- 3-5+ years of experience in AI/data engineering and implementation roles, including data engineering, machine learning, NLP, or Generative AI-focused data solutions.
PREFERRED QUALIFICATIONS:
- 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).
- 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.
This role offers the flexibility to be home-based anywhere in the U.S. with preference for the Eastern time zone. If you're near our Raleigh office, we follow a friendly hybrid model with three days a week in the office—great for collaboration and connection!
The base salary range budgeted for this position is $140,000 to $170,000. 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 EPEWA, the expected Application Deadline for this position is 7/1/2026 - this applies to both internal and external candidates.
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
GENERAL INFORMATION
Req #
WD00099074
Career area:
Artificial Intelligence
Country/Region:
United States of America
State:
North Carolina
City:
Morrisville
Date:
Wednesday, May 27, 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 #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Guided by its vision of “Smarter Technology for All”, Lenovo is executing a Hybrid AI strategy that spans Personal AI – one personal AI, multiple devices; and Enterprise AI – helping customers turn data into insights and value. This strategy is delivered through the Group’s commitment to world-class innovation and a full-stack AI portfolio, including devices (PCs, workstations, smartphones, tablets, accessories), infrastructure solutions (server, storage, edge, high performance computing and software defined infrastructure), as well as software, solutions, and services. With a global footprint spanning 21 research and development locations in 11 markets, and a global supply chain including more than 30 manufacturing sites across 10 markets, Lenovo is widely recognized for its operational excellence, including ranking #8 in the Gartner Supply Chain Top 25. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
DESCRIPTION AND REQUIREMENTS
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 role sits within Lenovo’s Solutions & Services Group (SSG), the global organization that brings together our end-to-end AI solutions and services to turn customer vision into value. You’ll be joining a new, distributed engineering team building the xIQ Agent Platform, an AI-native delivery platform that powers Lenovo’s Agentic AI strategy across hybrid cloud, on-prem, and edge.
- Design, develop, and implement data-driven AI solutions for an Agentic AI platform, aligning with enterprise architecture and business objectives.
- Build and maintain scalable data processing pipelines for AI workloads, including data ingestion, cleansing, transformation, and feature engineering.
- Develop and deploy end-to-end AI systems using LLMs, SLMs, and VLMs for advanced data processing, enrichment, and automation.
- Leverage NVIDIA AI technologies (e.g., CUDA, NV-Ingest, VLM..etc) or similar platforms to optimize model training, fine-tuning, and inference performance.
- Implement and manage vector databases such as Milvus, PostgreSQL (PGVector), or other vector stores to support semantic search, embeddings, and Retrieval-Augmented Generation (RAG) use cases.
- Design and optimize data and retrieval pipelines that integrate structured and unstructured data with LLM-based reasoning systems.
- Develop and integrate AI components (APIs, microservices, inference layers) into enterprise platforms across cloud, on-premise, and edge environments.
- Select and implement data engineering and pipeline orchestration tools to ensure scalable and reliable data workflows.
- Apply best practices in data engineering, MLOps, and AIOps, including pipeline monitoring, versioning, and performance tuning.
- Ensure data security, governance, and compliance, including encryption, access control, and secure data handling practices.
- Write clean, maintainable, and reusable code following enterprise development standards and best practices.
- Create detailed technical documentation, including data flow architectures, pipeline designs, model integration patterns, and system interfaces.
- Continuously evaluate and adopt emerging AI, LLM, and data technologies to improve solution effectiveness and scalability.
- Support solution design discussions, PoCs, and pre-sales activities by providing expertise in AI data architecture and implementation.
- Effectively communicate technical designs, data strategies, and AI solutions to both technical teams and business stakeholders.
BASIC QUALIFICATIONS:
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field.
- 3-5+ years of experience in AI/data engineering and implementation roles, including data engineering, machine learning, NLP, or Generative AI-focused data solutions.
PREFERRED QUALIFICATIONS:
- 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).
- 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.
This role offers the flexibility to be home-based anywhere in the U.S. with preference for the Eastern time zone. If you're near our Raleigh office, we follow a friendly hybrid model with three days a week in the office—great for collaboration and connection!
The base salary range budgeted for this position is $140,000 to $170,000. 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 EPEWA, the expected Application Deadline for this position is 7/1/2026 - this applies to both internal and external candidates.
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
See all STEM OPT AI Data Specialist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new STEM OPT AI Data Specialist Jobs.
Get Access To All JobsTips for Finding STEM OPT Authorization as an AI Data Specialist
Verify your CIP code before applying
Check that your degree's CIP code is on the STEM Designated Degree Program List maintained by ICE. Computer science (11.07), data science (11.04), and statistics (27.05) all qualify, but interdisciplinary AI programs can vary by institution.
Screen job postings for E-Verify enrollment
Before sending any application, confirm the employer is enrolled in E-Verify through the E-Verify employer search. Sponsors who aren't enrolled cannot legally hire STEM OPT students, and postings rarely flag this gap upfront.
Align your I-983 training plan to AI Data Specialist duties
Your I-983 must tie your training objectives to specific role tasks, such as data annotation, model evaluation, or pipeline QA. Vague plans get flagged by DSOs, so map each objective to a concrete deliverable your manager can describe.
Target employers with active LCA filings in AI roles
Use Migrate Mate to filter employers by Labor Condition Application filings under AI and data science job categories, so you're targeting companies that have already filed the DOL paperwork for roles matching your background.
Negotiate your start date around OPT cap-gap timing
If your initial 12-month OPT expires while an H-1B visa petition is pending, cap-gap rules let you keep working. Confirm your offer letter start date leaves enough lead time for your DSO to authorize the STEM OPT extension before your current EAD runs out.
Pull prevailing wage data before every offer evaluation
Run the AI Data Specialist SOC code through the OFLC Wage Search to see the Level I through Level IV prevailing wage for your metro area. Your offer must meet the prevailing wage for any future LCA your employer files.
Frequently Asked Questions
Does my degree qualify me for the STEM OPT extension as an AI Data Specialist?
Your degree qualifies if it carries a STEM-designated CIP code, such as computer science, data science, statistics, or a related engineering field. The role itself doesn't determine eligibility; your degree program does. Check the ICE STEM Designated Degree Program List against your transcript's CIP code, and confirm with your DSO before applying for positions.
What E-Verify requirement applies to my STEM OPT employer?
Every employer that hires a STEM OPT student must be enrolled in E-Verify at the specific worksite where you'll work. If your company uses a staffing agency or a third-party client site, the end client must also be enrolled. USCIS requires your DSO to confirm E-Verify enrollment before authorizing your STEM OPT extension, so verify this before accepting an offer.
What should the I-983 training plan include for an AI Data Specialist role?
Your I-983 must describe how the position provides practical training in your STEM field. For AI Data Specialist roles, that means listing specific learning objectives tied to tasks like data labeling methodologies, model performance evaluation, dataset quality assurance, or annotation pipeline management. Your supervisor must sign off on the plan, and your DSO reviews it for academic relevance before approving the extension.
How do I find AI Data Specialist jobs at companies enrolled in E-Verify?
Use Migrate Mate to search AI Data Specialist roles filtered for STEM OPT eligibility. The platform surfaces employers with verified E-Verify enrollment and active Labor Condition Application filings, so you're not spending time applying to companies that can't legally hire STEM OPT students. Standard job boards don't filter for E-Verify status, which makes this the most direct approach.
What happens to my STEM OPT work authorization if I receive an H-1B and my EAD expires before October 1?
Cap-gap protection automatically extends your work authorization if your H-1B petition is filed before your OPT EAD expires and your petition is selected in the lottery. You can keep working under cap-gap until October 1, when the new H-1B fiscal year begins. USCIS confirms cap-gap eligibility on your I-20, which your DSO updates once your employer files the H-1B petition.