Data Scientist Visa Sponsorship Jobs in Virginia
Virginia is one of the strongest states for data scientist visa sponsorship, anchored by a dense cluster of federal contractors, defense agencies, and tech firms in Northern Virginia and the DC metro corridor. Employers like Booz Allen Hamilton, Leidos, Capital One, and Amazon Web Services actively hire data scientists and have established H-1B sponsorship track records.
See All Data Scientist JobsOverview
Showing 5 of 61+ Data Scientist Jobs in Virginia with Visa Sponsorship jobs
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all 61+ Data Scientist Jobs in Virginia with Visa Sponsorship
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Data Scientist Jobs in Virginia with Visa Sponsorship.
Get Access To All JobsJob Title: Data Scientist Specialist
Locations: Onsite in Mclean, VA (5 days a week)
Job Description:
Must Have Qualifications:
- Must have 3+ years of hands-on experience with machine learning transitioned into GenAI.
- 10+ years of experience developing Angular Front End, React, Python based microservices, AWS, and Scaled Agile Framework (SAFe).
Preferred:
- Built AI agent, MCP, A2A, Graph Rag, deployed Gen AI applications to production.
Overview:
We are seeking a highly experienced Principal Gen AI Scientist with a strong focus on Generative AI (GenAI) to lead the design and development of cutting-edge AI Agents, Agentic Workflows and Gen AI Applications that solve complex business problems. This role requires advanced proficiency in Prompt Engineering, Large Language Models (LLMs), RAG, Graph RAG, MCP, A2A, multi-modal AI, Gen AI Patterns, Evaluation Frameworks, Guardrails, data curation, and AWS cloud deployments. You will serve as a hands-on Gen AI (data) scientist and critical thought leader, working alongside full stack developers, UX designers, product managers and data engineers to shape and implement enterprise-grade Gen AI solutions.
Key Responsibilities:
- Architect and implement scalable AI Agents, Agentic Workflows and GenAI applications to address diverse and complex business use cases.
- Develop, fine-tune, and optimize lightweight LLMs; lead the evaluation and adaptation of models such as Claude (Anthropic), Azure OpenAI, and open-source alternatives.
- Design and deploy Retrieval-Augmented Generation (RAG) and Graph RAG systems using vector databases and knowledge bases.
- Curate enterprise data using connectors integrated with AWS Bedrock's Knowledge Base/Elastic.
- Implement solutions leveraging MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication.
- Build and maintain Jupyter-based notebooks using platforms like SageMaker and MLFlow/Kubeflow on Kubernetes (EKS).
- Collaborate with cross-functional teams of UI and microservice engineers, designers, and data engineers to build full-stack Gen AI experiences.
- Integrate GenAI solutions with enterprise platforms via API-based methods and GenAI standardized patterns.
- Establish and enforce validation procedures with Evaluation Frameworks, bias mitigation, safety protocols, and guardrails for production-ready deployment.
- Design & build robust ingestion pipelines that extract, chunk, enrich, and anonymize data from PDFs, video, and audio sources for use in LLM-powered workflows—leveraging best practices like semantic chunking and privacy controls.
- Orchestrate multimodal pipelines using scalable frameworks (e.g., Apache Spark, PySpark) for automated ETL/ELT workflows appropriate for unstructured media.
- Implement embeddings drives—map media content to vector representations using embedding models, and integrate with vector stores (AWS Bedrock Knowledge Base/Elastic/Mongo Atlas) to support RAG architectures.
Required Qualifications:
- 10+ years of experience in AI/ML, with 3+ years in applied GenAI or LLM-based solutions.
- Deep expertise in prompt engineering, fine-tuning, RAG, GraphRAG, vector databases (e.g., AWS Bedrock Knowledge Base / Elastic), and multi-modal models.
- Proven experience with cloud-native AI development (AWS SageMaker, Bedrock, MLFlow on EKS).
- Strong programming skills in Python and ML libraries (Transformers, LangChain, etc.).
- Deep understanding of Gen AI system patterns and architectural best practices, Evaluation Frameworks.
- Demonstrated ability to work in cross-functional agile teams.
- Need GitHub Code Repository Link for each candidate. Please thoroughly vet the candidates.
Preferred Qualifications:
- Published contributions or patents in AI/ML/LLM domains.
- Hands-on experience with enterprise AI governance and ethical deployment frameworks.
- Familiarity with CI/CD practices for ML Ops and scalable inference APIs.
Zillion Technologies is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other characteristic protected by applicable federal, state, or local law.
Job Title: Data Scientist Specialist
Locations: Onsite in Mclean, VA (5 days a week)
Job Description:
Must Have Qualifications:
- Must have 3+ years of hands-on experience with machine learning transitioned into GenAI.
- 10+ years of experience developing Angular Front End, React, Python based microservices, AWS, and Scaled Agile Framework (SAFe).
Preferred:
- Built AI agent, MCP, A2A, Graph Rag, deployed Gen AI applications to production.
Overview:
We are seeking a highly experienced Principal Gen AI Scientist with a strong focus on Generative AI (GenAI) to lead the design and development of cutting-edge AI Agents, Agentic Workflows and Gen AI Applications that solve complex business problems. This role requires advanced proficiency in Prompt Engineering, Large Language Models (LLMs), RAG, Graph RAG, MCP, A2A, multi-modal AI, Gen AI Patterns, Evaluation Frameworks, Guardrails, data curation, and AWS cloud deployments. You will serve as a hands-on Gen AI (data) scientist and critical thought leader, working alongside full stack developers, UX designers, product managers and data engineers to shape and implement enterprise-grade Gen AI solutions.
Key Responsibilities:
- Architect and implement scalable AI Agents, Agentic Workflows and GenAI applications to address diverse and complex business use cases.
- Develop, fine-tune, and optimize lightweight LLMs; lead the evaluation and adaptation of models such as Claude (Anthropic), Azure OpenAI, and open-source alternatives.
- Design and deploy Retrieval-Augmented Generation (RAG) and Graph RAG systems using vector databases and knowledge bases.
- Curate enterprise data using connectors integrated with AWS Bedrock's Knowledge Base/Elastic.
- Implement solutions leveraging MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication.
- Build and maintain Jupyter-based notebooks using platforms like SageMaker and MLFlow/Kubeflow on Kubernetes (EKS).
- Collaborate with cross-functional teams of UI and microservice engineers, designers, and data engineers to build full-stack Gen AI experiences.
- Integrate GenAI solutions with enterprise platforms via API-based methods and GenAI standardized patterns.
- Establish and enforce validation procedures with Evaluation Frameworks, bias mitigation, safety protocols, and guardrails for production-ready deployment.
- Design & build robust ingestion pipelines that extract, chunk, enrich, and anonymize data from PDFs, video, and audio sources for use in LLM-powered workflows—leveraging best practices like semantic chunking and privacy controls.
- Orchestrate multimodal pipelines using scalable frameworks (e.g., Apache Spark, PySpark) for automated ETL/ELT workflows appropriate for unstructured media.
- Implement embeddings drives—map media content to vector representations using embedding models, and integrate with vector stores (AWS Bedrock Knowledge Base/Elastic/Mongo Atlas) to support RAG architectures.
Required Qualifications:
- 10+ years of experience in AI/ML, with 3+ years in applied GenAI or LLM-based solutions.
- Deep expertise in prompt engineering, fine-tuning, RAG, GraphRAG, vector databases (e.g., AWS Bedrock Knowledge Base / Elastic), and multi-modal models.
- Proven experience with cloud-native AI development (AWS SageMaker, Bedrock, MLFlow on EKS).
- Strong programming skills in Python and ML libraries (Transformers, LangChain, etc.).
- Deep understanding of Gen AI system patterns and architectural best practices, Evaluation Frameworks.
- Demonstrated ability to work in cross-functional agile teams.
- Need GitHub Code Repository Link for each candidate. Please thoroughly vet the candidates.
Preferred Qualifications:
- Published contributions or patents in AI/ML/LLM domains.
- Hands-on experience with enterprise AI governance and ethical deployment frameworks.
- Familiarity with CI/CD practices for ML Ops and scalable inference APIs.
Zillion Technologies is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other characteristic protected by applicable federal, state, or local law.
Data Scientist Job Roles in Virginia
See all 61+ Data Scientist Jobs in Virginia
Sign up for free to filter by visa type, set job alerts, and find employers with verified sponsorship history.
Search Data Scientist Jobs in VirginiaData Scientist Jobs in Virginia: Frequently Asked Questions
Which companies sponsor visas for data scientists in Virginia?
Northern Virginia's federal contracting sector produces the most consistent data scientist sponsorship activity in the state. Booz Allen Hamilton, Leidos, SAIC, and Peraton regularly file H-1B petitions for data science roles. Capital One's McLean headquarters and Amazon Web Services' Arlington presence add strong private-sector sponsorship. Defense-adjacent analytics firms concentrated around Tysons Corner and Reston also appear frequently in DOL disclosure data for data scientist positions.
Which visa types are most common for data scientist roles in Virginia?
The H-1B is by far the most common visa category for data scientists in Virginia, given that data science meets the specialty occupation standard requiring a bachelor's degree or higher in a directly related field such as computer science, statistics, or mathematics. Employers with established sponsorship programs may also support O-1A petitions for candidates with exceptional research records. Some positions at universities or research institutions qualify under J-1 or OPT extensions.
Which cities in Virginia have the most data scientist sponsorship jobs?
Northern Virginia dominates, particularly Arlington, McLean, Reston, and Tysons Corner, driven by federal contractors and major tech campuses. Richmond has a smaller but growing market tied to Capital One's operations and financial services firms. Virginia Beach and Norfolk see occasional openings through defense and maritime analytics contractors. For candidates prioritizing volume and employer diversity, the Northern Virginia corridor offers the most concentrated sponsorship activity in the state.
How to find data scientist visa sponsorship jobs in Virginia?
Migrate Mate filters job listings specifically by visa sponsorship availability, so you can search data scientist roles in Virginia without sifting through postings from employers who don't sponsor. The platform surfaces positions from federal contractors, tech firms, and financial services companies across Northern Virginia and beyond. Filtering by location and role on Migrate Mate is the most direct way to identify which Virginia employers are actively hiring sponsored data scientists right now.
Are there state-specific factors that affect data scientist sponsorship in Virginia?
Virginia's concentration of federal contracting work introduces a practical consideration: many data scientist roles require security clearances, which can limit sponsorship to candidates who are already permanent residents or citizens. Non-cleared positions are most common at commercial tech firms and financial institutions. Virginia's public universities, including Virginia Tech and George Mason University, also produce a consistent pipeline of data science graduates who enter the OPT-to-H-1B sponsorship pathway, so employers in the state are generally familiar with the process.
What is the prevailing wage for sponsored data scientist jobs in Virginia?
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.
See which data scientist employers are hiring and sponsoring visas in Virginia right now.
Search Data Scientist Jobs in Virginia