H-1B Visa Nlp Engineer Jobs
NLP Engineer roles qualify as H-1B visa specialty occupations under the computer and mathematical occupations category, requiring at least a bachelor's degree in computer science, computational linguistics, or a related field. Employers filing H-1B petitions for NLP engineers must certify a prevailing wage through a DOL Labor Condition Application before USCIS adjudicates the petition.
Find H-1B Visa Nlp Engineer JobsOverview
Showing 5 of 677+ Nlp Engineer jobs
See all 677+ Nlp Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Nlp Engineer roles.
Get Access To All JobsOur company
At Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.
What You’ll Do
We are building the next generation of AI-powered knowledge, reasoning, and autonomous agent platforms that operate at enterprise scale. We are seeking an exceptional Principal NLP Engineer to own and lead the design, development, and deployment of advanced natural language technologies powering semantic and context graphs, context analysis, intelligent search, retrieval, question answering, knowledge extraction, reasoning systems, AI agents, and enterprise copilots for Teradata Context Engine, our Autonomous Knowledge Platform. Context Engine is a platform that converts enterprise data estates into governed, agent-ready knowledge. Built for organizations where AI reliability and auditability are non-negotiable, Context Engine enables companies to deploy AI workflows on the data they already own — without rebuilding their infrastructure, without retraining their models, and without waiting for generic AI synthesis to learn the business terminology that took their analysts years to master.
This is a deeply hands-on technical leadership role for a recognized expert in Natural Language Processing who combines strong research foundations with proven experience shipping production systems that serve millions of users and process billions of documents. You will work at the intersection of large language models, information retrieval, knowledge graphs, semantic understanding, and agentic AI.
The ideal candidate has a track record of driving breakthrough NLP capabilities from research to production and possesses deep expertise across classical NLP, modern transformer architectures, retrieval-augmented generation (RAG), multimodal understanding, information extraction, and large-scale language model systems.
Technical Leadership
- Define and execute the strategic roadmap for NLP and language understanding capabilities across our Knowledge Platform.
- Serve as the technical authority for large-scale NLP architecture, algorithms, and production deployment.
- Drive innovation in enterprise language understanding, semantic search, retrieval systems, knowledge extraction, and AI reasoning.
NLP and Language Intelligence
- Design and build advanced NLP systems for:
- Entity extraction
- Relationship extraction
- Information extraction
- Document understanding
- Semantic indexing
- Context understanding and representation
- Text classification
- Topic modeling
- Summarization
- Question answering
- Conversational AI
- Knowledge grounding
- Multi-document reasoning
- Extracting context from multi-modal sources of language
- Multi-lingual solutions
- Machine translation
- Develop systems that transform unstructured enterprise content into structured knowledge assets.
- Advance techniques for long-context understanding, document intelligence, and multi-hop reasoning.
- Build domain-adaptive language understanding models across diverse enterprise data sources.
- Develop solutions with highest quality and performance.
- Develop solutions that are tested and validated.
Large Language Models
- Design and optimize applications built on frontier foundation models.
- Build advanced retrieval-augmented generation architectures for enterprise-scale environments.
- Develop agentic workflows that leverage LLMs for planning, reasoning, execution, and tool usage.
- Create evaluation methodologies that measure factuality, grounding, trustworthiness, and task completion.
- Improve model performance through prompt engineering, fine-tuning, continued pretraining, synthetic data generation, and reinforcement-learning-based approaches.
Knowledge and Semantic Systems
- Design NLP pipelines that power enterprise knowledge graphs and semantic layers.
- Develop ontology-aware language understanding systems.
- Build entity resolution, canonicalization, taxonomy mapping, and concept extraction capabilities.
- Connect language understanding with graph-based reasoning and enterprise knowledge discovery platforms.
Platform and Scale
- Build highly scalable distributed NLP systems processing petabytes of enterprise content.
- Optimize inference architectures for latency, throughput, cost efficiency, and reliability.
- Lead deployment strategies across on-prem, cloud-native, hybrid, and enterprise environments.
- Partner closely with platform engineering teams to operationalize NLP services at global scale.
Research and Innovation
- Stay at the forefront of advances in:
- Foundation models
- Agentic AI
- Retrieval systems
- Representation learning
- Deep learning
- Knowledge-enhanced language models
- Reasoning systems
- Publish, patent, contribute to open source, and represent the organization externally at premier AI conferences and industry events.
- Mentor senior engineers and help establish NLP engineering best practices across the company.
Who You’ll Work With
Partner with distinguished engineers, architects, researchers, and product leaders to shape the future of Teradata enterprise AI.
What Makes You a Qualified Candidate
- PhD or MS in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, NLP, or related field.
- 12+ years of software engineering experience, including 8+ years building production NLP and machine learning systems.
- Recognized industry leader in Natural Language Processing, Language AI, Search, Retrieval, or LLM-based systems.
- Deep hands-on expertise developing and deploying large-scale NLP systems in production.
Deep Expertise In
- Transformer architectures
- Large Language Models
- Retrieval-Augmented Generation (RAG)
- Semantic search
- Information retrieval
- Knowledge extraction
- Entity recognition
- Relation extraction
- Text understanding
- Conversational AI
- Machine learning
- Deep learning
- Representation learning
- Graph-enhanced NLP
- Vector search systems
- Knowledge graphs
Strong Programming Skills
- Python
- PyTorch
- TensorFlow/JAX
- Spark
- Distributed computing frameworks
Experience With
- Hugging Face ecosystem
- Fine-tuning and adaptation frameworks
- Large-scale model evaluation
- Vector databases
- Embedding models
- Search engines
- Knowledge graphs
- Distributed ML infrastructure
- AI observability and evaluation platforms
Preferred Qualifications
- PhD with published research in NLP, IR, ML, or AI in top-tier peer reviewed journals and conferences.
- Experience building systems that serve hundreds of millions of users or process billions of documents.
- Contributions to major NLP open-source ecosystems.
- Publications in ACL, EMNLP, NAACL, COLING, NeurIPS, ICML, ICLR, KDD, SIGIR, WWW, or related venues.
- Experience leading architecture for enterprise copilots, intelligent assistants, or autonomous agents.
- Expertise in enterprise search and knowledge management systems.
- Experience with graph-based reasoning and knowledge graph technologies.
- Patent portfolio in NLP, machine learning, search, or language understanding.
What You’ll Bring
- Established reputation as an industry expert in NLP and language AI.
- Proven record of taking breakthrough research into production at scale.
- Experience building state-of-the-art systems involving:
- Enterprise search
- Enterprise copilots
- Document intelligence
- Retrieval systems
- Knowledge extraction
- AI agents
- Semantic reasoning
- Knowledge graphs
- Ability to influence technical strategy across multiple organizations.
- Strong balance of scientific rigor, engineering excellence, and product impact.
Success Metrics
Within 12 months, you will:
- Define next-generation NLP and language intelligence architecture for the platform.
- Deliver measurable improvements in retrieval quality, answer accuracy, grounding, and user satisfaction.
- Establish world-class evaluation and benchmarking frameworks.
- Lead development of enterprise-scale knowledge extraction and semantic understanding capabilities.
- Enable agentic AI experiences that leverage enterprise knowledge with high trust, transparency, and precision.
- Raise the organization's NLP and AI capabilities to industry-leading levels.
Why We Think You'll Love Teradata
We prioritize a people-first culture because we know our people are at the very heart of our success. We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work. We focus on well-being because we care about our people and their ability to thrive both personally and professionally. We are committed to actively working to foster an inclusive environment that celebrates people for all of who they are.
US Pay Rate: $182,700.00 - $228,400.00 - $274,000.00 Annually
Starting pay for the successful applicant will depend on geographic location, internal equity, job-related knowledge, skills, and candidate experience. Sales roles will be eligible for commission payments tied to quota achievement. All other permanent roles will be eligible for one of our annual incentive plans, which are based on company financial attainment and individual performance. Employees in this position are eligible to participate in the Company’s benefits programs, which generally include health care, life and disability insurance, retirement savings, and time-off programs. Benefit details vary by country and plan, including eligibility and available options, and will be shared during the hiring process. Additional information is available here: https://www.teradata.com/About-Us/Careers/Benefits Employees in this position are also eligible to participate in the Company’s comprehensive benefits programs, which include healthcare, life and disability insurance plans, a 401(k)-retirement savings plan, and time-off programs. Specific details of these benefits, including eligibility criteria and plan options, will be provided during the hiring process and can be reviewed here: https://www.teradata.com/About-Us/Careers/Benefits
Teradata is proud to be an equal opportunity employer. We do not discriminate based upon race, color, ancestry, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related conditions), national origin, sexual orientation, age, citizenship, marital status, disability, medical condition, genetic information, gender identity or expression, military and veteran status, or any other legally protected status. We welcome and encourage individuals from all backgrounds to apply and join our team, bringing their unique perspectives and experiences to help us innovate and grow. If you require accommodations during the interview process, please let your recruiter know and we will work with you to meet your needs.
Our company
At Teradata, we believe that people thrive when empowered with better information. Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI.
What You’ll Do
We are building the next generation of AI-powered knowledge, reasoning, and autonomous agent platforms that operate at enterprise scale. We are seeking an exceptional Principal NLP Engineer to own and lead the design, development, and deployment of advanced natural language technologies powering semantic and context graphs, context analysis, intelligent search, retrieval, question answering, knowledge extraction, reasoning systems, AI agents, and enterprise copilots for Teradata Context Engine, our Autonomous Knowledge Platform. Context Engine is a platform that converts enterprise data estates into governed, agent-ready knowledge. Built for organizations where AI reliability and auditability are non-negotiable, Context Engine enables companies to deploy AI workflows on the data they already own — without rebuilding their infrastructure, without retraining their models, and without waiting for generic AI synthesis to learn the business terminology that took their analysts years to master.
This is a deeply hands-on technical leadership role for a recognized expert in Natural Language Processing who combines strong research foundations with proven experience shipping production systems that serve millions of users and process billions of documents. You will work at the intersection of large language models, information retrieval, knowledge graphs, semantic understanding, and agentic AI.
The ideal candidate has a track record of driving breakthrough NLP capabilities from research to production and possesses deep expertise across classical NLP, modern transformer architectures, retrieval-augmented generation (RAG), multimodal understanding, information extraction, and large-scale language model systems.
Technical Leadership
- Define and execute the strategic roadmap for NLP and language understanding capabilities across our Knowledge Platform.
- Serve as the technical authority for large-scale NLP architecture, algorithms, and production deployment.
- Drive innovation in enterprise language understanding, semantic search, retrieval systems, knowledge extraction, and AI reasoning.
NLP and Language Intelligence
- Design and build advanced NLP systems for:
- Entity extraction
- Relationship extraction
- Information extraction
- Document understanding
- Semantic indexing
- Context understanding and representation
- Text classification
- Topic modeling
- Summarization
- Question answering
- Conversational AI
- Knowledge grounding
- Multi-document reasoning
- Extracting context from multi-modal sources of language
- Multi-lingual solutions
- Machine translation
- Develop systems that transform unstructured enterprise content into structured knowledge assets.
- Advance techniques for long-context understanding, document intelligence, and multi-hop reasoning.
- Build domain-adaptive language understanding models across diverse enterprise data sources.
- Develop solutions with highest quality and performance.
- Develop solutions that are tested and validated.
Large Language Models
- Design and optimize applications built on frontier foundation models.
- Build advanced retrieval-augmented generation architectures for enterprise-scale environments.
- Develop agentic workflows that leverage LLMs for planning, reasoning, execution, and tool usage.
- Create evaluation methodologies that measure factuality, grounding, trustworthiness, and task completion.
- Improve model performance through prompt engineering, fine-tuning, continued pretraining, synthetic data generation, and reinforcement-learning-based approaches.
Knowledge and Semantic Systems
- Design NLP pipelines that power enterprise knowledge graphs and semantic layers.
- Develop ontology-aware language understanding systems.
- Build entity resolution, canonicalization, taxonomy mapping, and concept extraction capabilities.
- Connect language understanding with graph-based reasoning and enterprise knowledge discovery platforms.
Platform and Scale
- Build highly scalable distributed NLP systems processing petabytes of enterprise content.
- Optimize inference architectures for latency, throughput, cost efficiency, and reliability.
- Lead deployment strategies across on-prem, cloud-native, hybrid, and enterprise environments.
- Partner closely with platform engineering teams to operationalize NLP services at global scale.
Research and Innovation
- Stay at the forefront of advances in:
- Foundation models
- Agentic AI
- Retrieval systems
- Representation learning
- Deep learning
- Knowledge-enhanced language models
- Reasoning systems
- Publish, patent, contribute to open source, and represent the organization externally at premier AI conferences and industry events.
- Mentor senior engineers and help establish NLP engineering best practices across the company.
Who You’ll Work With
Partner with distinguished engineers, architects, researchers, and product leaders to shape the future of Teradata enterprise AI.
What Makes You a Qualified Candidate
- PhD or MS in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, NLP, or related field.
- 12+ years of software engineering experience, including 8+ years building production NLP and machine learning systems.
- Recognized industry leader in Natural Language Processing, Language AI, Search, Retrieval, or LLM-based systems.
- Deep hands-on expertise developing and deploying large-scale NLP systems in production.
Deep Expertise In
- Transformer architectures
- Large Language Models
- Retrieval-Augmented Generation (RAG)
- Semantic search
- Information retrieval
- Knowledge extraction
- Entity recognition
- Relation extraction
- Text understanding
- Conversational AI
- Machine learning
- Deep learning
- Representation learning
- Graph-enhanced NLP
- Vector search systems
- Knowledge graphs
Strong Programming Skills
- Python
- PyTorch
- TensorFlow/JAX
- Spark
- Distributed computing frameworks
Experience With
- Hugging Face ecosystem
- Fine-tuning and adaptation frameworks
- Large-scale model evaluation
- Vector databases
- Embedding models
- Search engines
- Knowledge graphs
- Distributed ML infrastructure
- AI observability and evaluation platforms
Preferred Qualifications
- PhD with published research in NLP, IR, ML, or AI in top-tier peer reviewed journals and conferences.
- Experience building systems that serve hundreds of millions of users or process billions of documents.
- Contributions to major NLP open-source ecosystems.
- Publications in ACL, EMNLP, NAACL, COLING, NeurIPS, ICML, ICLR, KDD, SIGIR, WWW, or related venues.
- Experience leading architecture for enterprise copilots, intelligent assistants, or autonomous agents.
- Expertise in enterprise search and knowledge management systems.
- Experience with graph-based reasoning and knowledge graph technologies.
- Patent portfolio in NLP, machine learning, search, or language understanding.
What You’ll Bring
- Established reputation as an industry expert in NLP and language AI.
- Proven record of taking breakthrough research into production at scale.
- Experience building state-of-the-art systems involving:
- Enterprise search
- Enterprise copilots
- Document intelligence
- Retrieval systems
- Knowledge extraction
- AI agents
- Semantic reasoning
- Knowledge graphs
- Ability to influence technical strategy across multiple organizations.
- Strong balance of scientific rigor, engineering excellence, and product impact.
Success Metrics
Within 12 months, you will:
- Define next-generation NLP and language intelligence architecture for the platform.
- Deliver measurable improvements in retrieval quality, answer accuracy, grounding, and user satisfaction.
- Establish world-class evaluation and benchmarking frameworks.
- Lead development of enterprise-scale knowledge extraction and semantic understanding capabilities.
- Enable agentic AI experiences that leverage enterprise knowledge with high trust, transparency, and precision.
- Raise the organization's NLP and AI capabilities to industry-leading levels.
Why We Think You'll Love Teradata
We prioritize a people-first culture because we know our people are at the very heart of our success. We embrace a flexible work model because we trust our people to make decisions about how, when, and where they work. We focus on well-being because we care about our people and their ability to thrive both personally and professionally. We are committed to actively working to foster an inclusive environment that celebrates people for all of who they are.
US Pay Rate: $182,700.00 - $228,400.00 - $274,000.00 Annually
Starting pay for the successful applicant will depend on geographic location, internal equity, job-related knowledge, skills, and candidate experience. Sales roles will be eligible for commission payments tied to quota achievement. All other permanent roles will be eligible for one of our annual incentive plans, which are based on company financial attainment and individual performance. Employees in this position are eligible to participate in the Company’s benefits programs, which generally include health care, life and disability insurance, retirement savings, and time-off programs. Benefit details vary by country and plan, including eligibility and available options, and will be shared during the hiring process. Additional information is available here: https://www.teradata.com/About-Us/Careers/Benefits Employees in this position are also eligible to participate in the Company’s comprehensive benefits programs, which include healthcare, life and disability insurance plans, a 401(k)-retirement savings plan, and time-off programs. Specific details of these benefits, including eligibility criteria and plan options, will be provided during the hiring process and can be reviewed here: https://www.teradata.com/About-Us/Careers/Benefits
Teradata is proud to be an equal opportunity employer. We do not discriminate based upon race, color, ancestry, religion, creed, sex (including pregnancy, childbirth, breastfeeding, or related conditions), national origin, sexual orientation, age, citizenship, marital status, disability, medical condition, genetic information, gender identity or expression, military and veteran status, or any other legally protected status. We welcome and encourage individuals from all backgrounds to apply and join our team, bringing their unique perspectives and experiences to help us innovate and grow. If you require accommodations during the interview process, please let your recruiter know and we will work with you to meet your needs.
See all 677+ H-1B Visa Nlp Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa Nlp Engineer Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as a Nlp Engineer
Verify your degree supports specialty occupation
USCIS scrutinizes NLP roles when your degree is in a broad field like information systems. Pull the O*NET profile for NLP or machine learning engineers and confirm your transcripts show coursework directly tied to that occupation code.
Target employers with active LCA filing history
Search Migrate Mate to filter NLP Engineer roles by employers who have filed Labor Condition Applications for this occupation. LCA history confirms the employer has navigated H-1B sponsorship before, cutting your risk of a first-timer filing error.
Understand how your role title affects wage levels
DOL assigns prevailing wages by SOC code and experience tier. An NLP Engineer titled 'Research Scientist' may land at a higher wage level than 'Software Engineer II,' affecting your offer negotiation. Use the OFLC Wage Search to check the level your job description maps to.
Document proprietary model work for RFE defense
USCIS increasingly issues Requests for Evidence on NLP roles, questioning whether the work is truly specialized. Before filing, build a paper trail: architecture diagrams, model cards, and peer-review citations that show your day-to-day tasks require graduate-level NLP expertise.
Negotiate cap-exempt employer options before the lottery
Universities, nonprofit research labs, and certain government contractors are cap-exempt, meaning you can start any time without waiting for the October 1 start date. If you're on OPT and your registration isn't selected, a cap-exempt NLP role lets you stay in status immediately.
Align your start date with cap-gap protection
If your F-1 OPT expires before October 1 after a successful H-1B lottery selection, cap-gap automatically extends your work authorization. Your employer must file the I-129 before your OPT end date, so confirm their filing timeline well before that deadline.
H-1B Visa Nlp Engineer: Frequently Asked Questions
Does an NLP Engineer role qualify as a specialty occupation for H-1B purposes?
Yes. USCIS classifies NLP Engineer positions under computer and mathematical occupations, which routinely satisfy the specialty occupation standard because the work theoretically and practically requires at least a bachelor's degree in computer science, computational linguistics, or a directly related field. Employers strengthen petitions by mapping job duties to graduate-level NLP tasks such as transformer architecture design, corpus annotation methodology, or low-resource language modeling.
How do employers determine the prevailing wage for an H-1B NLP Engineer petition?
Employers use the DOL's OFLC Wage Search to identify the prevailing wage for your SOC code, experience level, and work location before certifying the Labor Condition Application. NLP Engineers often map to the software developers or computer research scientists SOC code depending on duties, and the wage level assigned affects what the employer must pay. You can verify expected wage levels yourself using the OFLC Wage Search before negotiating an offer.
Which employers are most likely to sponsor H-1B visas for NLP Engineer roles?
Technology companies building conversational AI, search, and language model products file the highest volume of H-1B LCAs for NLP-related occupations. Academic medical centers, financial services firms building document processing tools, and defense contractors also sponsor regularly. Migrate Mate filters NLP Engineer roles by verified LCA filing history so you can identify employers who have sponsored this specific occupation, not just tech employers broadly.
Can I switch employers mid-H-1B if I get a better NLP Engineer offer?
Yes. Under H-1B portability rules established by AC21, you can change employers once you've been in H-1B status for at least 180 days and your new employer files an H-1B transfer petition before your current status expires. Your work authorization continues while the transfer petition is pending. The new employer must file a fresh LCA at the prevailing wage for your new work location, which matters if you're moving between high- and lower-cost metro areas.
What happens to my H-1B status if my NLP Engineer role is eliminated in a layoff?
You enter a 60-day grace period from your last day of employment, during which you can find a new sponsor, change to a different nonimmigrant status, or depart the U.S. Your former employer is responsible for the cost of return transportation to your home country under USCIS regulations. During those 60 days, a new employer can file an H-1B transfer petition and you can begin working once it's filed, not just approved, if you have at least 180 days of prior H-1B time.