Applied AI Engineer Jobs in USA with Visa Sponsorship
Applied AI Engineers qualify for H-1B visa, O-1A, and EB-2 NIW visas based on their specialized machine learning expertise. Most positions require a computer science or related STEM degree, though the 3-for-1 experience rule can substitute. Major tech companies actively sponsor these roles. For detailed occupation requirements, see the O*NET profile.
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About Quizlet:
At Quizlet, our mission is to help every learner achieve their outcomes in the most effective and delightful way. We’re a $1B+ learning platform used by two-thirds of U.S. high school students and half of college students, powering over 1 billion learning interactions each week.
We blend cognitive science with machine learning to personalize and enhance the learning experience for students, professionals, and lifelong learners alike. We’re energized by the potential to power more learners through multiple approaches and various tools. Let’s Build the Future of Learning
Join us to design and deliver AI-powered learning tools that scale across the world and unlock human potential.
About the Team (Applied AI):
Our mission is to invent and deploy the next generation of intelligent, personalized, and adaptive learning experiences. We’re consolidating AI efforts across the company into a unified portfolio and are accountable for a disproportionate share of Quizlet’s growth and product differentiation. You’ll partner closely with Product, Data Science, and the AI & Data Platform to deliver an AI-driven learning coach that’s recognized as best-in-class.
About the Role:
We are looking for Applied AI Engineers ranging from the Senior to Staff as well as Sr. Staff levels (note: leveling decisions made through the interview process).
You’ll be working at the forefront of our AI strategy, shaping Quizlet’s AI development in one of the two complementary domains:
Personalization & Ranking – retrieval and ranking systems that match learners with the right content, experiences, and monetization moments across surfaces (search, feed, notifications, ads).
Generative AI & Agentic Systems – LLM-powered tutoring, content understanding/synthesis, and tools that boost learner outcomes and creator productivity.
You will work on a variety of models and modeling systems (from Two-Tower retrieval and multi-task rankers to RAG/LLM pipelines), ensure robust evaluation, and responsible deployment.
We’re happy to share that this is an onsite position in either our Denver, San Francisco, Seattle, or NYC. To help foster team collaboration, we require that employees be in the office a minimum of three days per week: Monday, Wednesday, and Thursday and as needed by your manager or the company. We believe that this working environment facilitates increased work efficiency, team partnership, and supports growth as an employee and organization.
In this role, you will:
- Contribute to the technical roadmap for applied AI across personalization, ranking, search, recommendations, and GenAI/LLM systems; help connect modeling work to business metrics (engaged learners, conversion, retention, revenue)
- Build components of end-to-end ML systems: candidate sourcing, embedding platforms & ANN retrieval, multi-stage ranking (early/late), and value modeling with guardrails for fairness and integrity
- Implement LLM-based features: build RAG pipelines, apply instruction-/preference-tuning techniques (e.g., SFT/DPO), optimize prompts, and improve latency/cost-aware inference; contribute to offline evals + human-in-the-loop and online success metrics
- Help develop "Learner 360" representations by working with behavior signals, explicit inputs, and conversational context to create robust embeddings reused across surfaces
- Support evaluation infrastructure: contribute to the eval harness for both ranking and generative systems (offline metrics like NDCG/AUC/BLEU/BERTScore; quality/safety scorecards), and help close the loop with online A/B experiments
- Ship reliable systems at scale: ensure training-serving consistency, implement drift detection, follow canarying/rollback protocols, participate in on-call rotation for model services, and maintain strong CI/CD for features & models
- Collaborate with and learn from senior ML/SWE teammates; write high-quality code and follow best practices for experimentation rigor and reproducibility
- Work closely with Product, Design, Legal, and Data Science on objectives, tradeoffs, and responsible AI practices
- Stay current with ML research (RecSys, LLMs, multimodal) and propose new methods that could improve learner outcomes
What you bring to the table:
- 6+ years of industry experience in applied ML/AI or ML-heavy software engineering
- BS/MS in CS, ML, or related quantitative field (or equivalent experience)
- Experience building ranking/personalization or search systems (retrieval, Two-Tower/dual encoders, multi-task rankers) and contributing to online metric improvements (e.g., CTR, session depth, retention)
- Hands-on experience with LLM/GenAI systems: data curation, fine-tuning (SFT/PEFT, preference optimization), prompt engineering, evaluation, and productionization considerations (latency/cost/safety)
- Strong skills in Python/PyTorch, data and feature engineering, distributed training/inference on GPUs, and familiarity with modern MLOps (model registry, feature stores, monitoring, drift)
- Solid experiment design (offline/online), metrics literacy, and ability to translate product goals into modeling solutions
- Strong collaboration skills and eagerness to learn from senior engineers; some experience mentoring junior teammates is a plus
Bonus points if you have:
- EdTech or consumer mobile experience; conversational tutoring or learning science-informed modeling
- Publications/open-source with RecSys/LLMs (e.g., RecSys, KDD, NeurIPS, ICLR, ACL), or contributions to safety/guardrails tooling
- Experience building on a modern MLOps stack (feature mgmt, orchestration, streaming, online inference at scale)
Compensation, Benefits & Perks:
- Quizlet is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Salary transparency helps to mitigate unfair hiring practices when it comes to discrimination and pay gaps. Total compensation for this role is market competitive, including a starting base salary of $178,000 - $330,000 depending on location and experience, as well as company stock options
- Collaborate with your manager and team to create a healthy work-life balance
- 20 vacation days that we expect you to take!
- Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice)
- Employer-sponsored 401k plan with company match
- Access to LinkedIn Learning and other resources to support professional growth
- Paid Family Leave, FSA, HSA, Commuter benefits, and Wellness benefits
- 40 hours of annual paid time off to participate in volunteer programs of choice
Why Join Quizlet?
🌎 Massive reach: 60M+ users, 1B+ interactions per week
🤖 Cutting-edge tech: Generative AI, adaptive learning, cognitive science
📈 Strong momentum: Top-tier investors, sustainable business, real traction
🎨 Mission-first: Work that makes a difference in people’s lives
🤝 Inclusive culture: Committed to equity, diversity, and belonging We strive to make everyone feel comfortable and welcome!
We work to create a holistic interview process, where both Quizlet and candidates have an opportunity to view what it would be like to work together, in exploring a mutually beneficial partnership.
We provide a transparent setting that gives a comprehensive view of who we are!
In Closing:
At Quizlet, we’re excited about passionate people joining our team—even if you don’t check every box on the requirements list. We value unique perspectives and believe everyone has something meaningful to contribute. Our culture is all about taking initiative, learning through challenges, and striving for high-quality work while staying curious and open to new ideas. We believe in honest, respectful communication, thoughtful collaboration, and creating a supportive space where everyone can grow and succeed together.
Quizlet’s success as an online learning community depends on a strong commitment to diversity, equity, and inclusion.
As an equal opportunity employer and a tech company committed to societal change, we welcome applicants from all backgrounds. Women, people of color, members of the LGBTQ+ community, individuals with disabilities, and veterans are strongly encouraged to apply. Come join us!
To All Recruiters and Placement Agencies:
At this time, Quizlet does not accept unsolicited agency resumes and/or profiles. Please do not forward unsolicited agency resumes to our website or to any Quizlet employee. Quizlet will not pay fees to any third-party agency or firm nor will it be responsible for any agency fees associated with unsolicited resumes. All unsolicited resumes received will be considered the property of Quizlet.
LI-onsite
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

About Quizlet:
At Quizlet, our mission is to help every learner achieve their outcomes in the most effective and delightful way. We’re a $1B+ learning platform used by two-thirds of U.S. high school students and half of college students, powering over 1 billion learning interactions each week.
We blend cognitive science with machine learning to personalize and enhance the learning experience for students, professionals, and lifelong learners alike. We’re energized by the potential to power more learners through multiple approaches and various tools. Let’s Build the Future of Learning
Join us to design and deliver AI-powered learning tools that scale across the world and unlock human potential.
About the Team (Applied AI):
Our mission is to invent and deploy the next generation of intelligent, personalized, and adaptive learning experiences. We’re consolidating AI efforts across the company into a unified portfolio and are accountable for a disproportionate share of Quizlet’s growth and product differentiation. You’ll partner closely with Product, Data Science, and the AI & Data Platform to deliver an AI-driven learning coach that’s recognized as best-in-class.
About the Role:
We are looking for Applied AI Engineers ranging from the Senior to Staff as well as Sr. Staff levels (note: leveling decisions made through the interview process).
You’ll be working at the forefront of our AI strategy, shaping Quizlet’s AI development in one of the two complementary domains:
Personalization & Ranking – retrieval and ranking systems that match learners with the right content, experiences, and monetization moments across surfaces (search, feed, notifications, ads).
Generative AI & Agentic Systems – LLM-powered tutoring, content understanding/synthesis, and tools that boost learner outcomes and creator productivity.
You will work on a variety of models and modeling systems (from Two-Tower retrieval and multi-task rankers to RAG/LLM pipelines), ensure robust evaluation, and responsible deployment.
We’re happy to share that this is an onsite position in either our Denver, San Francisco, Seattle, or NYC. To help foster team collaboration, we require that employees be in the office a minimum of three days per week: Monday, Wednesday, and Thursday and as needed by your manager or the company. We believe that this working environment facilitates increased work efficiency, team partnership, and supports growth as an employee and organization.
In this role, you will:
- Contribute to the technical roadmap for applied AI across personalization, ranking, search, recommendations, and GenAI/LLM systems; help connect modeling work to business metrics (engaged learners, conversion, retention, revenue)
- Build components of end-to-end ML systems: candidate sourcing, embedding platforms & ANN retrieval, multi-stage ranking (early/late), and value modeling with guardrails for fairness and integrity
- Implement LLM-based features: build RAG pipelines, apply instruction-/preference-tuning techniques (e.g., SFT/DPO), optimize prompts, and improve latency/cost-aware inference; contribute to offline evals + human-in-the-loop and online success metrics
- Help develop "Learner 360" representations by working with behavior signals, explicit inputs, and conversational context to create robust embeddings reused across surfaces
- Support evaluation infrastructure: contribute to the eval harness for both ranking and generative systems (offline metrics like NDCG/AUC/BLEU/BERTScore; quality/safety scorecards), and help close the loop with online A/B experiments
- Ship reliable systems at scale: ensure training-serving consistency, implement drift detection, follow canarying/rollback protocols, participate in on-call rotation for model services, and maintain strong CI/CD for features & models
- Collaborate with and learn from senior ML/SWE teammates; write high-quality code and follow best practices for experimentation rigor and reproducibility
- Work closely with Product, Design, Legal, and Data Science on objectives, tradeoffs, and responsible AI practices
- Stay current with ML research (RecSys, LLMs, multimodal) and propose new methods that could improve learner outcomes
What you bring to the table:
- 6+ years of industry experience in applied ML/AI or ML-heavy software engineering
- BS/MS in CS, ML, or related quantitative field (or equivalent experience)
- Experience building ranking/personalization or search systems (retrieval, Two-Tower/dual encoders, multi-task rankers) and contributing to online metric improvements (e.g., CTR, session depth, retention)
- Hands-on experience with LLM/GenAI systems: data curation, fine-tuning (SFT/PEFT, preference optimization), prompt engineering, evaluation, and productionization considerations (latency/cost/safety)
- Strong skills in Python/PyTorch, data and feature engineering, distributed training/inference on GPUs, and familiarity with modern MLOps (model registry, feature stores, monitoring, drift)
- Solid experiment design (offline/online), metrics literacy, and ability to translate product goals into modeling solutions
- Strong collaboration skills and eagerness to learn from senior engineers; some experience mentoring junior teammates is a plus
Bonus points if you have:
- EdTech or consumer mobile experience; conversational tutoring or learning science-informed modeling
- Publications/open-source with RecSys/LLMs (e.g., RecSys, KDD, NeurIPS, ICLR, ACL), or contributions to safety/guardrails tooling
- Experience building on a modern MLOps stack (feature mgmt, orchestration, streaming, online inference at scale)
Compensation, Benefits & Perks:
- Quizlet is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Salary transparency helps to mitigate unfair hiring practices when it comes to discrimination and pay gaps. Total compensation for this role is market competitive, including a starting base salary of $178,000 - $330,000 depending on location and experience, as well as company stock options
- Collaborate with your manager and team to create a healthy work-life balance
- 20 vacation days that we expect you to take!
- Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice)
- Employer-sponsored 401k plan with company match
- Access to LinkedIn Learning and other resources to support professional growth
- Paid Family Leave, FSA, HSA, Commuter benefits, and Wellness benefits
- 40 hours of annual paid time off to participate in volunteer programs of choice
Why Join Quizlet?
🌎 Massive reach: 60M+ users, 1B+ interactions per week
🤖 Cutting-edge tech: Generative AI, adaptive learning, cognitive science
📈 Strong momentum: Top-tier investors, sustainable business, real traction
🎨 Mission-first: Work that makes a difference in people’s lives
🤝 Inclusive culture: Committed to equity, diversity, and belonging We strive to make everyone feel comfortable and welcome!
We work to create a holistic interview process, where both Quizlet and candidates have an opportunity to view what it would be like to work together, in exploring a mutually beneficial partnership.
We provide a transparent setting that gives a comprehensive view of who we are!
In Closing:
At Quizlet, we’re excited about passionate people joining our team—even if you don’t check every box on the requirements list. We value unique perspectives and believe everyone has something meaningful to contribute. Our culture is all about taking initiative, learning through challenges, and striving for high-quality work while staying curious and open to new ideas. We believe in honest, respectful communication, thoughtful collaboration, and creating a supportive space where everyone can grow and succeed together.
Quizlet’s success as an online learning community depends on a strong commitment to diversity, equity, and inclusion.
As an equal opportunity employer and a tech company committed to societal change, we welcome applicants from all backgrounds. Women, people of color, members of the LGBTQ+ community, individuals with disabilities, and veterans are strongly encouraged to apply. Come join us!
To All Recruiters and Placement Agencies:
At this time, Quizlet does not accept unsolicited agency resumes and/or profiles. Please do not forward unsolicited agency resumes to our website or to any Quizlet employee. Quizlet will not pay fees to any third-party agency or firm nor will it be responsible for any agency fees associated with unsolicited resumes. All unsolicited resumes received will be considered the property of Quizlet.
LI-onsite
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
See all 597+ Applied AI Engineer jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Applied AI Engineer roles.
Get Access To All JobsTips for Finding Visa Sponsorship as an Applied AI Engineer
Target ML-focused companies with established sponsorship programs
Companies like Google, Meta, Microsoft, and NVIDIA regularly sponsor Applied AI Engineers. Their dedicated immigration teams understand the specialized nature of ML roles and visa requirements.
Emphasize your specialized AI/ML training and certifications
Highlight advanced coursework in neural networks, deep learning frameworks, and MLOps. Specialized training demonstrates the technical expertise required for H-1B specialty occupation requirements.
Document your experience with production ML systems
Experience deploying models at scale, optimizing inference performance, and building ML pipelines shows specialized knowledge that supports visa petitions and distinguishes you from general software roles.
Consider the EB-2 NIW pathway for advanced AI research
If you have publications, patents, or contributions to open-source AI frameworks, the National Interest Waiver provides a direct green card path without employer sponsorship.
Apply early in the fiscal year for H-1B cap-subject positions
H-1B registration opens in March for April lottery. Cap-exempt employers like universities and research institutions offer year-round opportunities without lottery constraints.
Build a portfolio showcasing deployed AI applications
GitHub repositories, technical blogs, and deployed models demonstrate your specialized expertise. This documentation strengthens both job applications and visa petition evidence requirements.
Applied AI Engineer jobs are hiring across the US. Find yours.
Find Applied AI Engineer JobsFrequently Asked Questions
Do Applied AI Engineers qualify for H-1B visa sponsorship?
Yes, Applied AI Engineers typically qualify for H-1B sponsorship as the role requires specialized knowledge in machine learning, neural networks, and AI frameworks. You'll need a bachelor's degree in computer science, mathematics, engineering, or related field. The position must demonstrate specialty occupation requirements through complex AI/ML responsibilities.
Can I get sponsored without a computer science degree?
Yes, degrees in mathematics, statistics, physics, or engineering can qualify if combined with relevant AI/ML coursework or experience. The 3-for-1 rule allows three years of specialized AI experience to substitute for one year of education. Certifications in TensorFlow, PyTorch, or cloud ML platforms strengthen your case.
How to find Applied AI Engineer jobs with visa sponsorship?
To find Applied AI Engineer jobs with visa sponsorship, use Migrate Mate, which specializes in connecting international talent with sponsoring employers. Focus on tech companies, startups, and consulting firms that commonly hire AI engineers for H-1B, L-1, or O-1 visas. These roles are in high demand across industries like healthcare, finance, and autonomous vehicles.
Which visa is best for Applied AI Engineers with research experience?
The EB-2 NIW (National Interest Waiver) is ideal if you have AI research publications, patents, or contributions to significant ML projects. It provides a direct path to a green card without employer sponsorship. O-1A visas work for those with extraordinary ability in AI research or industry recognition.
What's the H-1B approval rate for AI and ML positions?
Computer occupations, including AI/ML roles, have approximately 85-90% H-1B approval rates when properly documented. Denials typically occur when job duties aren't sufficiently specialized or degree requirements aren't clearly established. Strong LCA documentation and detailed role descriptions improve approval odds significantly.
Can Applied AI Engineers transfer H-1B status between employers?
Yes, H-1B portability allows you to start working for a new employer once they file your H-1B transfer petition (Form I-129). You don't need to wait for approval. The new position must still qualify as a specialty occupation with appropriate degree requirements and AI/ML responsibilities.
What is the prevailing wage requirement for sponsored Applied AI 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.
See which Applied AI Engineer employers are hiring and sponsoring visas right now.
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