Learning Specialist Jobs in USA with Visa Sponsorship
Learning Specialist roles qualify for H-1B visa sponsorship as specialty occupations requiring educational technology or instructional design expertise. Employers like Amazon, Microsoft, and Google regularly sponsor Learning Specialists for H-1B, E-3 visa, and TN visas. The position demands specialized knowledge in learning management systems, curriculum development, and training methodologies. For detailed occupation requirements, see the O*NET profile.
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Get Access To All JobsAbout Glean:
Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles.
At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level.
Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality.
If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.
About the Role:
Glean is seeking a Machine Learning Engineer to improve the quality of our AI Assistant and autonomous agents. This role sits at the intersection of production machine learning, LLM-powered systems, and product engineering, with a focus on building, evaluating, and iterating on assistant experiences that are useful, reliable, and grounded in real enterprise workflows.
You will work on applied problems across agent quality, evaluation, personalization, retrieval, and orchestration. The ideal person is excited by shipping production systems, not pure research, and wants to help shape how Glean’s assistant gets better over time through stronger signals, tighter feedback loops, and better end-to-end execution quality.
You will:
- Build and improve ML and LLM-powered systems that raise the quality of Glean’s AI Assistant and autonomous agents across real user workflows.
- Design evaluation, benchmarking, and monitoring loops to measure assistant quality, model quality, and end-to-end system performance.
- Develop and iterate on signals, prompts, workflows, and model-driven logic that improve reasoning, planning, personalization, and task completion quality.
- Work across areas such as RAG, semantic search, recommendation-style systems, post-training or reinforcement learning, and agent orchestration where they materially improve product outcomes.
- Partner closely with product, design, and engineering teammates to understand customer pain points and ship high-quality production systems quickly.
- Contribute to the data and ML infrastructure needed to support robust experimentation, offline and online evaluation, and continuous model improvement.
About you:
- 2+ years of industry experience in machine learning, applied AI, or software engineering with significant ML ownership.
- Strong hands-on coding ability and a track record of shipping production systems, not just prototypes or research projects.
- Experience in one or more of the following areas: LLM applications, NLP, search, retrieval, recommendations, evaluation frameworks, agent systems, or personalization.
- Comfort working across both modeling and product engineering details, including experimentation, quality measurement, and production iteration.
- Proficiency in common ML tooling and strong software engineering fundamentals in languages such as Python, Go, Java, or C++.
- A pragmatic, product-minded approach. You know when to use sophisticated ML techniques and when simple, reliable systems are the better answer.
- A proactive, low-ego working style and excitement about learning quickly in a high-velocity environment.
Location:
- This role is hybrid (4 days a week in our San Francisco office)
Compensation & Benefits:
The standard base salary range for this position is $180,000 - $205,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.
We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused.
We’re committed to building and sustaining a diverse, inclusive workplace. We strive to attract and retain people with a wide range of backgrounds, experiences, and perspectives, and we do not discriminate on the basis of gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.
LI-HYBRID
AI-First Mindset at Glean:
At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required.
Global Data Privacy Notice for Job Candidates and Applicants:
Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy. By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement.
About Glean:
Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles.
At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level.
Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality.
If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.
About the Role:
Glean is seeking a Machine Learning Engineer to improve the quality of our AI Assistant and autonomous agents. This role sits at the intersection of production machine learning, LLM-powered systems, and product engineering, with a focus on building, evaluating, and iterating on assistant experiences that are useful, reliable, and grounded in real enterprise workflows.
You will work on applied problems across agent quality, evaluation, personalization, retrieval, and orchestration. The ideal person is excited by shipping production systems, not pure research, and wants to help shape how Glean’s assistant gets better over time through stronger signals, tighter feedback loops, and better end-to-end execution quality.
You will:
- Build and improve ML and LLM-powered systems that raise the quality of Glean’s AI Assistant and autonomous agents across real user workflows.
- Design evaluation, benchmarking, and monitoring loops to measure assistant quality, model quality, and end-to-end system performance.
- Develop and iterate on signals, prompts, workflows, and model-driven logic that improve reasoning, planning, personalization, and task completion quality.
- Work across areas such as RAG, semantic search, recommendation-style systems, post-training or reinforcement learning, and agent orchestration where they materially improve product outcomes.
- Partner closely with product, design, and engineering teammates to understand customer pain points and ship high-quality production systems quickly.
- Contribute to the data and ML infrastructure needed to support robust experimentation, offline and online evaluation, and continuous model improvement.
About you:
- 2+ years of industry experience in machine learning, applied AI, or software engineering with significant ML ownership.
- Strong hands-on coding ability and a track record of shipping production systems, not just prototypes or research projects.
- Experience in one or more of the following areas: LLM applications, NLP, search, retrieval, recommendations, evaluation frameworks, agent systems, or personalization.
- Comfort working across both modeling and product engineering details, including experimentation, quality measurement, and production iteration.
- Proficiency in common ML tooling and strong software engineering fundamentals in languages such as Python, Go, Java, or C++.
- A pragmatic, product-minded approach. You know when to use sophisticated ML techniques and when simple, reliable systems are the better answer.
- A proactive, low-ego working style and excitement about learning quickly in a high-velocity environment.
Location:
- This role is hybrid (4 days a week in our San Francisco office)
Compensation & Benefits:
The standard base salary range for this position is $180,000 - $205,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.
We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused.
We’re committed to building and sustaining a diverse, inclusive workplace. We strive to attract and retain people with a wide range of backgrounds, experiences, and perspectives, and we do not discriminate on the basis of gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.
LI-HYBRID
AI-First Mindset at Glean:
At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required.
Global Data Privacy Notice for Job Candidates and Applicants:
Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy. By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement.
See all 3,164+ Learning Specialist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Learning Specialist roles.
Get Access To All JobsTips for Finding Visa Sponsorship as a Learning Specialist
Target companies with established L&D programs
Focus on tech companies, consulting firms, and Fortune 500 organizations with dedicated learning and development departments. These employers understand the specialized skills required and have existing sponsorship processes.
Emphasize instructional design credentials
Highlight certifications in ADDIE, SAM methodology, or specific LMS platforms like Cornerstone OnDemand or Workday Learning. These technical qualifications strengthen your specialty occupation case for visa approval.
Document measurable learning outcomes
Prepare examples showing training program effectiveness, completion rates, and skill assessment improvements. USCIS wants evidence that your role requires specialized knowledge beyond general training coordination.
Consider corporate university positions
McDonald's Hamburger University, GE's Crotonville, and similar corporate education centers frequently sponsor visas. These roles clearly demonstrate the specialized nature of organizational learning design.
Leverage e-learning and digital expertise
Experience with Articulate Storyline, Adobe Captivate, or VR training platforms differentiates you from general trainers. Technical learning development skills align well with H-1B specialty occupation requirements.
Network through learning professional associations
Join ATD (Association for Talent Development) local chapters and attend CLO Exchange events. Many corporate learning leaders at visa-sponsoring companies are active in these professional communities.
Frequently Asked Questions
Do Learning Specialist positions qualify for H-1B sponsorship?
Yes, Learning Specialist roles typically qualify as specialty occupations when they require expertise in instructional design, educational technology, or training program development. The position must demonstrate specialized knowledge beyond basic training coordination. Employers need to show the role requires at least a bachelor's degree in education, instructional technology, or related field.
What degree is required for Learning Specialist visa sponsorship?
Most employers require a bachelor's degree in Education, Instructional Design, Educational Technology, Psychology, or Human Resources Development. Some positions accept related fields like Communications or Business with relevant learning and development experience. Advanced degrees in Educational Technology or Training Design strengthen your application significantly.
Which visa types work best for Learning Specialists?
H-1B visa is the primary option for most nationalities, with good approval rates for qualified candidates. Australians can use the E-3 visa with less competition. Canadians and Mexicans may qualify for TN status under the Scientific Technician category if the role involves educational research or curriculum development with clear scientific applications.
How do I prove specialty occupation requirements as a Learning Specialist?
Document your use of specialized learning management systems, instructional design methodologies like ADDIE or SAM, and training evaluation frameworks. Provide examples of curriculum development, learning analytics, or educational technology implementation. Certifications from ATD, ISPI, or specific LMS platforms strengthen your case considerably.
What companies typically sponsor Learning Specialists for work visas?
Technology companies (Microsoft, Amazon, Google), consulting firms (Deloitte, PwC, McKinsey), and large corporations with dedicated learning divisions frequently sponsor visas. Healthcare systems, financial services firms, and companies with corporate universities also regularly hire sponsored Learning Specialists. Focus on organizations with 500+ employees and formal L&D departments.
How to find Learning Specialist jobs with visa sponsorship?
To find Learning Specialist jobs with visa sponsorship, use Migrate Mate, which specializes in connecting international candidates with sponsoring employers. Focus your search on educational technology companies, corporate training departments, and multinational organizations that frequently sponsor H-1B, O-1 visa, or other work visas for learning and development professionals with specialized expertise in instructional design and educational program management.
What is the prevailing wage requirement for sponsored Learning Specialist 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.