Nlp Engineer Jobs in USA with Visa Sponsorship
NLP Engineer roles consistently rank among the most H-1B visa-sponsored positions in tech, with employers like Google, Amazon, and Microsoft filing hundreds of petitions annually. Most require a master's or PhD in computer science or computational linguistics, and specialty occupation status is well-established for this role. For detailed occupation requirements, see the O*NET profile.
Find Nlp Engineer JobsOverview
Showing 5 of 15,177+ Nlp Engineer jobs
See all 15,177+ 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 15,177+ 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 JobsTips for Finding Visa Sponsorship as a Nlp Engineer
Target companies with active LCA filings
Large tech firms and AI-focused startups file Labor Condition Applications publicly. Prioritize employers with a track record of NLP-specific sponsorships rather than companies sponsoring their first technical hire, approval timelines and success rates differ significantly.
Lead with your specialty, not just 'NLP'
Employers sponsoring NLP roles need to demonstrate specialty occupation. Framing your expertise around a specific domain, conversational AI, information extraction, or machine translation, strengthens the petition and signals clear alignment between your degree and the role.
A master's degree changes your H-1B odds
NLP Engineers with a U.S. master's or higher qualify for the advanced degree exemption, giving you two lottery chances instead of one. This meaningfully increases selection probability, a distinction worth understanding before your first H-1B registration.
OPT and STEM OPT are real runway, not just a gap
Computer science and linguistics degrees both qualify for 24-month STEM OPT extensions. That gives you up to three years of work authorization post-graduation, enough time to build a track record, survive a lottery miss, and position for sponsorship.
Document your research outputs before interviews
Publications, patents, and open-source contributions directly support O-1A and EB-1A petition criteria. Employers sponsoring NLP roles in research-heavy environments increasingly view these outputs as assets that reduce immigration risk and support stronger petitions.
Ask about sponsorship policy before the offer stage
Some employers sponsor H-1B transfers but not new cap-subject petitions. Confirming a company's exact sponsorship scope early, before investing in a full interview process, saves significant time and prevents offer-stage surprises with immigration implications.
Frequently Asked Questions
Is NLP Engineer considered a specialty occupation for H-1B purposes?
Yes. NLP Engineer consistently qualifies as a specialty occupation because the role requires at minimum a bachelor's degree in a specific field, typically computer science, computational linguistics, or a closely related discipline. USCIS has approved large volumes of H-1B visa petitions for this job title, and the degree-to-role connection is well established in petition precedent.
Do I need a master's degree to get sponsored as an NLP Engineer?
A bachelor's degree in computer science or computational linguistics meets the minimum H-1B specialty occupation threshold. However, most NLP roles at top employers, particularly in research, large language models, and applied AI, are filled by candidates with a master's or PhD. A U.S. master's degree also qualifies you for the advanced degree exemption pool, giving you two H-1B lottery chances instead of one.
Which visa types can NLP Engineers use besides H-1B?
Australians can pursue the E-3 visa, which has no lottery and is renewable indefinitely. Canadian and Mexican nationals may qualify under TN visa status if the role maps to a covered USMCA category. NLP Engineers with an extensive publication record or recognized contributions to the field may also qualify for the O-1A extraordinary ability visa, which bypasses the H-1B cap entirely.
How do I find NLP Engineer jobs that offer visa sponsorship?
Migrate Mate lists NLP Engineer roles specifically filtered for visa sponsorship, so you're not guessing which employers are open to it. The platform is built for international candidates, meaning you won't waste applications on postings that exclude sponsored candidates. Roles span large tech companies, AI startups, and research institutions, all with verified sponsorship intent.
Can my research experience substitute for a traditional degree in an NLP sponsorship petition?
In some cases, yes. USCIS allows three years of specialized training or experience to substitute for one year of formal education under the specialty occupation framework. For an NLP Engineer without a four-year degree, this means roughly 12 years of directly relevant experience could satisfy the requirement, though this path faces higher scrutiny and benefits from strong supporting documentation, including publications, patents, or employer letters detailing the complexity of the work.
What is the prevailing wage requirement for sponsored Nlp Engineer 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.