H-1B Visa AI Research Scientist Jobs
AI Research Scientist roles qualify as H-1B visa specialty occupations under the computer and mathematical sciences category, requiring at least a bachelor's degree in a directly related field. Most positions at research labs, tech companies, and universities fall under SOC code 15-2051, and many employers file premium processing to meet competitive hiring timelines.
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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 looking for a Senior Manager – AI Platform to lead the development and evolution of our next-generation platform powering autonomous, AI-driven agents. This role is ideal for a leader who combines data science expertise and technical depth, agentic platform thinking, and strategic execution to scale a distributed system that enables reasoning, planning, memory, and tool use at runtime.
As the Senior Manager, you will be responsible for driving product and data science strategy, overseeing a multidisciplinary team of engineers and data scientists, collaborating with AI/ML research and product teams, and ensuring that the AI Platform is performant, extensible, and production-ready.
Job Responsibilities:
- Lead the engineering and data science roadmap for the AI Platform, ensuring architectural scalability, reliability, and seamless integration with LLMs, data science pipelines.
- Partner with product, data science, research, and engineering teams to define requirements for capabilities such as predictive modeling, memory, planning, multi-agent collaboration, and tool orchestration.
- Drive the design and implementation of core platform services including API gateways, vector store integrations, RAG pipelines, and data science experimentation frameworks.
- Oversee integrations with third-party tools, internal data science services, and infrastructure platforms to enable real-world agent execution and model deployment at scale.
- Guide the team in applying best practices in cloud-native development, distributed computing, observability, and security.
- Manage, mentor, and grow a high-performing team of backend engineers, data scientists, and AI platform specialists.
- Ensure alignment between platform capabilities and evolving needs from AI product lines and downstream applications.
- Drive technical excellence through code and design reviews, system reliability practices, and collaboration across engineering functions.
- Contribute to the long-term vision and strategy of how agentic workflows, powered by data science and machine learning, will operate at scale across the organization.
What makes you a qualified candidate
- 12+ years of experience in software/platform engineering or data science, with 3+ years in engineering management or technical leadership roles overseeing AI-driven initiatives.
- Proven experience building and scaling distributed systems or cloud platforms in production environments.
- Strong technical background in backend development, APIs, infrastructure, or platform architecture.
- Hands-on experience with AI/ML platforms, LLM integrations, and demonstrated background in data science methodologies including model development, evaluation, and deployment.
- Proven experience working with vector databases, semantic search, feature stores, and end-to-end data science pipelines in production environments.
- Strong project management skills, with a track record of delivering large cross-functional initiatives.
- Excellent communication and collaboration skills, with the ability to work closely with executive stakeholders, researchers, and engineers.
- Passion for building platforms that enable intelligent, autonomous behavior at scale.
What you'll bring
- A strong track record of leading platform engineering and data science teams that build scalable, reliable systems supporting internal and external developers or AI/ML workloads.
- Deep understanding of software architecture, distributed systems, and cloud-native infrastructure — with the ability to make strategic technical decisions.
- Experience working at the intersection of AI, data science, and engineering, ideally supporting LLM-based products, AI agents, or data science platforms that deliver measurable business value.
- A pragmatic approach to balancing technical depth with delivery speed, especially in fast-paced, R&D-heavy environments.
- Demonstrated ability to hire, mentor, and retain high-performing engineers while fostering a culture of ownership, experimentation, and accountability.
- Strong cross-functional collaboration skills — able to partner effectively with product managers, researchers, infrastructure teams, and executive stakeholders.
- Curiosity and drive to push the boundaries of autonomous, data-science-powered software, and a clear vision for how data science and agentic AI systems will shape the next generation of enterprise applications.
- Excellent written and verbal communication skills, with the ability to articulate complex ideas clearly to technical and non-technical audiences.
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.
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 looking for a Senior Manager – AI Platform to lead the development and evolution of our next-generation platform powering autonomous, AI-driven agents. This role is ideal for a leader who combines data science expertise and technical depth, agentic platform thinking, and strategic execution to scale a distributed system that enables reasoning, planning, memory, and tool use at runtime.
As the Senior Manager, you will be responsible for driving product and data science strategy, overseeing a multidisciplinary team of engineers and data scientists, collaborating with AI/ML research and product teams, and ensuring that the AI Platform is performant, extensible, and production-ready.
Job Responsibilities:
- Lead the engineering and data science roadmap for the AI Platform, ensuring architectural scalability, reliability, and seamless integration with LLMs, data science pipelines.
- Partner with product, data science, research, and engineering teams to define requirements for capabilities such as predictive modeling, memory, planning, multi-agent collaboration, and tool orchestration.
- Drive the design and implementation of core platform services including API gateways, vector store integrations, RAG pipelines, and data science experimentation frameworks.
- Oversee integrations with third-party tools, internal data science services, and infrastructure platforms to enable real-world agent execution and model deployment at scale.
- Guide the team in applying best practices in cloud-native development, distributed computing, observability, and security.
- Manage, mentor, and grow a high-performing team of backend engineers, data scientists, and AI platform specialists.
- Ensure alignment between platform capabilities and evolving needs from AI product lines and downstream applications.
- Drive technical excellence through code and design reviews, system reliability practices, and collaboration across engineering functions.
- Contribute to the long-term vision and strategy of how agentic workflows, powered by data science and machine learning, will operate at scale across the organization.
What makes you a qualified candidate
- 12+ years of experience in software/platform engineering or data science, with 3+ years in engineering management or technical leadership roles overseeing AI-driven initiatives.
- Proven experience building and scaling distributed systems or cloud platforms in production environments.
- Strong technical background in backend development, APIs, infrastructure, or platform architecture.
- Hands-on experience with AI/ML platforms, LLM integrations, and demonstrated background in data science methodologies including model development, evaluation, and deployment.
- Proven experience working with vector databases, semantic search, feature stores, and end-to-end data science pipelines in production environments.
- Strong project management skills, with a track record of delivering large cross-functional initiatives.
- Excellent communication and collaboration skills, with the ability to work closely with executive stakeholders, researchers, and engineers.
- Passion for building platforms that enable intelligent, autonomous behavior at scale.
What you'll bring
- A strong track record of leading platform engineering and data science teams that build scalable, reliable systems supporting internal and external developers or AI/ML workloads.
- Deep understanding of software architecture, distributed systems, and cloud-native infrastructure — with the ability to make strategic technical decisions.
- Experience working at the intersection of AI, data science, and engineering, ideally supporting LLM-based products, AI agents, or data science platforms that deliver measurable business value.
- A pragmatic approach to balancing technical depth with delivery speed, especially in fast-paced, R&D-heavy environments.
- Demonstrated ability to hire, mentor, and retain high-performing engineers while fostering a culture of ownership, experimentation, and accountability.
- Strong cross-functional collaboration skills — able to partner effectively with product managers, researchers, infrastructure teams, and executive stakeholders.
- Curiosity and drive to push the boundaries of autonomous, data-science-powered software, and a clear vision for how data science and agentic AI systems will shape the next generation of enterprise applications.
- Excellent written and verbal communication skills, with the ability to articulate complex ideas clearly to technical and non-technical audiences.
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.
See all 1,779+ H-1B Visa AI Research Scientist Jobs
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Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an AI Research Scientist
Verify your degree meets specialty occupation
Your degree field must directly relate to AI research, not just computer science broadly. A PhD in statistics or cognitive science can qualify, but you'll need to document the connection to your specific role in the H-1B petition.
Search LCA filings by occupation code
Use Migrate Mate to filter employers by H-1B Labor Condition Application filings under SOC code 15-2051. This shows you which companies have actively sponsored AI Research Scientist roles, not just tech companies that sponsor H-1Bs generally.
Target cap-exempt employers for faster timelines
Universities, nonprofit research institutions, and government research organizations are cap-exempt, meaning they can file your H-1B petition any time of year without waiting for the April lottery. This matters if your OPT or other status expires soon.
Confirm prevailing wage level before negotiating
Look up your offered role's wage level using the OFLC Wage Search before finalizing your offer. Employers must certify your salary meets the DOL prevailing wage for your location and job duties, and Level I wages are frequently challenged for research positions.
Prepare publications and project documentation early
USCIS scrutinizes AI Research Scientist petitions for specialty occupation eligibility. Gather published papers, conference presentations, patent filings, and technical reports before your employer files. Strong evidence of specialized research output reduces RFE risk significantly.
Ask about premium processing at the offer stage
Many AI Research Scientist offers are time-sensitive because employers are competing for the same candidates. USCIS premium processing upgrades standard adjudication to 15 business days. Clarify whether your employer includes this in the sponsorship package before you sign.
H-1B Visa AI Research Scientist: Frequently Asked Questions
Does an AI Research Scientist role qualify as an H-1B specialty occupation?
Yes. AI Research Scientist positions fall under the computer and mathematical occupations category and require at least a bachelor's degree in a directly related field such as computer science, mathematics, or statistics. USCIS evaluates whether the specific job duties require theoretical and practical application of highly specialized knowledge, which most research-focused AI roles satisfy.
Which types of employers sponsor H-1B visas for AI Research Scientists?
Technology companies, national laboratories, university research departments, and AI-focused startups are the most active sponsors. Cap-exempt employers like universities and nonprofit research institutions can file outside the annual lottery window, which is a meaningful advantage. You can browse verified sponsoring employers on Migrate Mate, filtered by occupation code and filing history.
How does the H-1B lottery affect AI Research Scientist candidates at for-profit companies?
For-profit employers must enter the annual H-1B lottery, with registrations typically opening in March for an October 1 start date. Selection is not guaranteed. Candidates with a U.S. master's degree or higher get a second chance in the advanced-degree pool, which modestly improves selection odds. If not selected, some candidates pivot to cap-exempt roles to bridge the gap.
What documentation strengthens an H-1B petition for an AI Research Scientist?
Published research papers, conference proceedings, patents, technical reports, and letters from collaborators all support the specialty occupation argument. USCIS looks for evidence that the role requires a specific body of highly specialized knowledge. A strong job description that ties research duties to degree requirements is as important as your personal credentials.
Can I switch employers during H-1B status as an AI Research Scientist?
Yes. Under H-1B portability rules, you can start working for a new employer once they file a non-frivolous H-1B transfer petition, without waiting for approval. The new employer must file a fresh LCA with DOL and submit a new I-129 petition to USCIS. Your job duties and salary at the new employer must still meet specialty occupation and prevailing wage requirements.