Green Card Nlp Engineer Jobs
NLP Engineer roles qualify for EB-2 and EB-3 green card sponsorship through PERM labor certification, which requires your employer to document that no qualified U.S. worker is available before filing an I-140 petition on your behalf. Demand for NLP specialists in AI, search, and conversational systems has made this one of the more active job titles in employment-based sponsorship pipelines.
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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 674+ Green Card Nlp Engineer Jobs
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Get Access To All JobsTips for Finding Green Card Sponsorship as a Nlp Engineer
Translate your NLP credentials for PERM
PERM requires your employer to define a minimum degree requirement tied to the role. Make sure your transcript shows coursework in computational linguistics, machine learning, or statistics so your credentials map cleanly to the posted job requirements.
Target employers with active PERM filings
Search DOL OFLC disclosure data to find companies that have filed PERM applications specifically for NLP or machine learning engineer titles. Prior filings signal that the employer already has a sponsorship workflow and won't be starting from scratch for you.
Use Migrate Mate to find green card sponsors
Filter your NLP Engineer job search on Migrate Mate to surface employers with documented EB-2 and EB-3 sponsorship history. This cuts out the guesswork of cold-applying to companies that have never run a PERM case for this role type.
Clarify EB-2 versus EB-3 before accepting an offer
EB-2 requires the employer to justify an advanced degree requirement for the role. If your target company posts NLP positions requiring only a bachelor's degree, your case may route through EB-3. Knowing this before negotiation affects your green card timeline.
Verify your prevailing wage tier early
Use the OFLC Wage Search to look up the prevailing wage for NLP Engineer under the relevant Standard Occupational Classification code before your offer stage. Your employer must pay at or above that wage level throughout the PERM and I-140 process.
Confirm the employer's recruitment documentation timeline
PERM requires your employer to complete DOL-mandated recruitment steps before filing, typically over 30 to 180 days. Ask HR whether they have a standard recruitment documentation process or if this would be their first PERM filing for an NLP role.
Green Card Nlp Engineer: Frequently Asked Questions
Do NLP Engineer roles typically qualify for EB-2 or EB-3 sponsorship?
Both are possible depending on how the employer defines the job requirements. If the role requires a master's degree or a bachelor's plus substantial specialized experience in computational linguistics or machine learning, EB-2 is the more common route. EB-3 applies when the posted minimum is a bachelor's degree. The O*NET profile for this occupation lists a master's as the typical entry-level education, which supports EB-2 framing in most cases.
How does green card sponsorship differ from H-1B for an NLP Engineer?
H-1B visa is temporary, subject to an annual cap and lottery, and must be renewed. Green card sponsorship through PERM and I-140 is permanent and has no annual cap at the EB-2 or EB-3 petition level, though visa number availability by country affects final green card issuance. The PERM process also takes longer upfront, often 18 to 36 months from start to approval, but the outcome is lawful permanent residency rather than a fixed-term work authorization.
How do I find NLP Engineer jobs where the employer will sponsor a green card?
Search on Migrate Mate, which filters specifically for employers with EB-2 and EB-3 sponsorship history in technical roles. Many NLP positions are posted without explicit mention of green card sponsorship even when the employer is willing, so filtering by documented PERM filing history gives you a more accurate picture than reading job descriptions alone.
What does my employer need to do before filing the PERM labor certification?
Your employer must complete a DOL-mandated recruitment process to demonstrate that no qualified U.S. worker applied for the role. This typically involves posting the job for at least 30 days, running specific advertisements, and documenting why any U.S. applicants were not hired. For NLP Engineer positions, the employer must also define a specific minimum degree requirement tied to the job duties, which becomes the baseline for your I-140 filing.
Can I switch NLP Engineer jobs while my green card case is pending?
Yes, under portability rules established by AC21, you can change employers once your I-485 adjustment of status application has been pending for at least 180 days, as long as the new role is in the same or a similar occupational classification. NLP Engineer and adjacent machine learning or AI engineering titles generally fall within the same SOC classification, but you should confirm the new role aligns before making a move.