Machine Learning Scientist Jobs in USA with Visa Sponsorship
Machine learning scientist roles consistently rank among the highest for H-1B visa sponsorship, with tech companies regularly filing petitions for ML engineers, research scientists, and AI specialists. The role's advanced degree requirements and specialized skillset align perfectly with specialty occupation criteria, making visa approval rates favorable for qualified candidates. For detailed occupation requirements, see the O*NET profile.
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Salary Range: $207,900 - $219,450 per year. Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the annual base salary only and do not include equity.
About this role
We are looking for an experienced Machine Learning Scientist III to join our content recommendations team. In this role, you will be at the core of building and optimizing ML-based recommender systems (e.g., image and content recommendations, homepage and email optimization and personalization) to enhance the customer experience at Wayfair. Your work will directly impact how millions of customers discover and engage with products, driving significant business value.
As part of Wayfair's SMART (Search, Marketing, and Recommendations Technology) team, you will collaborate with ML scientists, engineers, and product teams to develop and deploy cutting-edge recommendation models that operate at scale. This role is an opportunity to solve complex problems related to personalization, large-scale machine learning, latency, and scalability while leveraging state-of-the-art (SOTA) AI techniques.
What you’ll do
- Develop and optimize recommendation models that power personalized experiences across Wayfair’s site, app, email, and push notifications.
- Conduct applied research to improve recommender systems using traditional ML techniques, deep learning and reinforcement learning.
- Build scalable ML pipelines for training, evaluation, and inference, ensuring models operate efficiently in production.
- Work closely with engineering teams to deploy models in a production environment, addressing real-world constraints such as latency, interpretability, and scalability.
- Analyze model performance and iterate based on A/B test results, offline evaluation metrics, and business impact.
- Leverage and contribute to open-source ML frameworks while staying up to date with cutting-edge research in recommendation systems.
- Drive innovation by identifying opportunities to improve personalization strategies and developing novel algorithms that enhance customer engagement.
- Collaborate with cross-functional teams including product managers, software engineers, and data scientists to align ML objectives with business goals.
- Mentor other less experienced scientists on the team.
Who you are
- 5+ years of experience developing and deploying machine learning models, with a focus on recommendations, ranking, or personalization.
- Strong theoretical understanding of machine learning and deep learning applied to large-scale recommendation problems.
- Experience in training, evaluating, and optimizing recommendation models in production, leveraging techniques such as collaborative filtering, sequence modeling, representation learning and multi-armed bandits.
- Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
- Familiarity with big data processing (Spark, Hadoop) and ML pipeline orchestration (Airflow, Kubeflow, MLflow).
- Strong coding skills and familiarity with building scalable ML systems in cloud environments (AWS, GCP, Azure).
- Ability to design experiments and analyze results using A/B testing and statistical techniques.
- Excellent communication skills, with the ability to explain complex ML concepts to non-technical stakeholders and drive data-driven decisions.
Nice to have
- Experience developing core recommendation systems for eCommerce, marketplaces, or streaming platforms.
- Familiarity with reinforcement learning or contextual bandits for adaptive recommendation strategies.
This role offers the opportunity to work on high-impact ML problems at scale, shaping the future of personalization and recommendations at Wayfair. If you're passionate about building intelligent systems that enhance customer experiences, we’d love to hear from you!
Why You'll Love Wayfair:
- Time Off:
- Paid Holidays
-
Paid Time Off (PTO)
-
Health & Wellness:
- Full Health Benefits (Medical, Dental, Vision, HSA/FSA)
- Life Insurance
- Disability Protection (Short Term & Long Term Disability)
- Global Wellbeing: Gym/Fitness discounts (including US Peloton, Global ClassPass, and various regional gym memberships)
- Mental Health Support (Global Mental Health, Global Wayhealthy Recordings)
-
Caregiver Services
-
Financial Growth & Security:
- 401K Matching (Employee Matching Program)
- Tuition Reimbursement
- Financial Health Education (Knowledge of Financial Education - KOFE)
-
Tax Advantaged Accounts
-
Family Support:
- Family Planning Support
- Parental Leave
-
Global Surrogacy & Adoption Policy
-
Professional Development & Recognition:
- Rewards & Recognition
- Global Employee Anniversary Awards
-
Paid Volunteer Work
-
Unique Perks:
- Employee Discount
- U.S. Bluebikes Membership
-
Global Pod Outings
-
Work/Life Balance:
- Emphasizing a supportive & flexible work environment that encourages a balance between personal and professional commitments.
Wayfair's In-Office Policy:
All Mountain View-based interns, co-ops, and corporate employees will be in office in a hybrid capacity. Employees will work in the office on designated days, Tuesday, Wednesday, and Thursday, and work remotely the other 2 days of the week.
Assistance for Individuals with Disabilities
Wayfair is fully committed to providing equal opportunities for all individuals, including individuals with disabilities. As part of this commitment, Wayfair will make reasonable accommodations to the known physical or mental limitations of qualified individuals with disabilities, unless doing so would impose an undue hardship on business operations. If you require a reasonable accommodation to participate in the job application or interview process, please let us know by completing our Accomodations for Applicants form.
Need Technical Assistance?
For more information about applying for a career at Wayfair, visit our FAQ page here.
About Wayfair Inc.
Wayfair is one of the world’s largest online destinations for the home. Whether you work in our global headquarters in Boston, or in our warehouses or offices throughout the world, we’re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you’re looking for rapid growth, constant learning, and dynamic challenges, then you’ll find that amazing career opportunities are knocking.
No matter who you are, Wayfair is a place you can call home. We’re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair – and world – for all. Every voice, every perspective matters. That’s why we’re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, genetic information, or any other legally protected characteristic.
Your personal data is processed in accordance with our Candidate Privacy Notice. If you have any questions or wish to exercise your rights under applicable privacy and data protection laws, please contact us at dataprotectionofficer@wayfair.com.

Salary Range: $207,900 - $219,450 per year. Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the annual base salary only and do not include equity.
About this role
We are looking for an experienced Machine Learning Scientist III to join our content recommendations team. In this role, you will be at the core of building and optimizing ML-based recommender systems (e.g., image and content recommendations, homepage and email optimization and personalization) to enhance the customer experience at Wayfair. Your work will directly impact how millions of customers discover and engage with products, driving significant business value.
As part of Wayfair's SMART (Search, Marketing, and Recommendations Technology) team, you will collaborate with ML scientists, engineers, and product teams to develop and deploy cutting-edge recommendation models that operate at scale. This role is an opportunity to solve complex problems related to personalization, large-scale machine learning, latency, and scalability while leveraging state-of-the-art (SOTA) AI techniques.
What you’ll do
- Develop and optimize recommendation models that power personalized experiences across Wayfair’s site, app, email, and push notifications.
- Conduct applied research to improve recommender systems using traditional ML techniques, deep learning and reinforcement learning.
- Build scalable ML pipelines for training, evaluation, and inference, ensuring models operate efficiently in production.
- Work closely with engineering teams to deploy models in a production environment, addressing real-world constraints such as latency, interpretability, and scalability.
- Analyze model performance and iterate based on A/B test results, offline evaluation metrics, and business impact.
- Leverage and contribute to open-source ML frameworks while staying up to date with cutting-edge research in recommendation systems.
- Drive innovation by identifying opportunities to improve personalization strategies and developing novel algorithms that enhance customer engagement.
- Collaborate with cross-functional teams including product managers, software engineers, and data scientists to align ML objectives with business goals.
- Mentor other less experienced scientists on the team.
Who you are
- 5+ years of experience developing and deploying machine learning models, with a focus on recommendations, ranking, or personalization.
- Strong theoretical understanding of machine learning and deep learning applied to large-scale recommendation problems.
- Experience in training, evaluating, and optimizing recommendation models in production, leveraging techniques such as collaborative filtering, sequence modeling, representation learning and multi-armed bandits.
- Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
- Familiarity with big data processing (Spark, Hadoop) and ML pipeline orchestration (Airflow, Kubeflow, MLflow).
- Strong coding skills and familiarity with building scalable ML systems in cloud environments (AWS, GCP, Azure).
- Ability to design experiments and analyze results using A/B testing and statistical techniques.
- Excellent communication skills, with the ability to explain complex ML concepts to non-technical stakeholders and drive data-driven decisions.
Nice to have
- Experience developing core recommendation systems for eCommerce, marketplaces, or streaming platforms.
- Familiarity with reinforcement learning or contextual bandits for adaptive recommendation strategies.
This role offers the opportunity to work on high-impact ML problems at scale, shaping the future of personalization and recommendations at Wayfair. If you're passionate about building intelligent systems that enhance customer experiences, we’d love to hear from you!
Why You'll Love Wayfair:
- Time Off:
- Paid Holidays
-
Paid Time Off (PTO)
-
Health & Wellness:
- Full Health Benefits (Medical, Dental, Vision, HSA/FSA)
- Life Insurance
- Disability Protection (Short Term & Long Term Disability)
- Global Wellbeing: Gym/Fitness discounts (including US Peloton, Global ClassPass, and various regional gym memberships)
- Mental Health Support (Global Mental Health, Global Wayhealthy Recordings)
-
Caregiver Services
-
Financial Growth & Security:
- 401K Matching (Employee Matching Program)
- Tuition Reimbursement
- Financial Health Education (Knowledge of Financial Education - KOFE)
-
Tax Advantaged Accounts
-
Family Support:
- Family Planning Support
- Parental Leave
-
Global Surrogacy & Adoption Policy
-
Professional Development & Recognition:
- Rewards & Recognition
- Global Employee Anniversary Awards
-
Paid Volunteer Work
-
Unique Perks:
- Employee Discount
- U.S. Bluebikes Membership
-
Global Pod Outings
-
Work/Life Balance:
- Emphasizing a supportive & flexible work environment that encourages a balance between personal and professional commitments.
Wayfair's In-Office Policy:
All Mountain View-based interns, co-ops, and corporate employees will be in office in a hybrid capacity. Employees will work in the office on designated days, Tuesday, Wednesday, and Thursday, and work remotely the other 2 days of the week.
Assistance for Individuals with Disabilities
Wayfair is fully committed to providing equal opportunities for all individuals, including individuals with disabilities. As part of this commitment, Wayfair will make reasonable accommodations to the known physical or mental limitations of qualified individuals with disabilities, unless doing so would impose an undue hardship on business operations. If you require a reasonable accommodation to participate in the job application or interview process, please let us know by completing our Accomodations for Applicants form.
Need Technical Assistance?
For more information about applying for a career at Wayfair, visit our FAQ page here.
About Wayfair Inc.
Wayfair is one of the world’s largest online destinations for the home. Whether you work in our global headquarters in Boston, or in our warehouses or offices throughout the world, we’re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you’re looking for rapid growth, constant learning, and dynamic challenges, then you’ll find that amazing career opportunities are knocking.
No matter who you are, Wayfair is a place you can call home. We’re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair – and world – for all. Every voice, every perspective matters. That’s why we’re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, genetic information, or any other legally protected characteristic.
Your personal data is processed in accordance with our Candidate Privacy Notice. If you have any questions or wish to exercise your rights under applicable privacy and data protection laws, please contact us at dataprotectionofficer@wayfair.com.
See all 1,112+ Machine Learning Scientist jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Scientist roles.
Get Access To All JobsTips for Finding Visa Sponsorship as a Machine Learning Scientist
Target companies with active ML research divisions
Focus on employers like Google DeepMind, Microsoft Research, OpenAI, and Meta AI. These companies regularly sponsor visas for ML scientists and understand the specialized nature of the role.
Emphasize your advanced degree in a relevant field
Machine learning scientist positions typically require at least a master's degree in computer science, statistics, mathematics, or related field. PhD holders have stronger visa petition cases.
Highlight specialized ML frameworks and research experience
Document expertise in TensorFlow, PyTorch, scikit-learn, and published research. USCIS recognizes ML as a specialty occupation requiring specific technical knowledge and advanced training.
Consider both tech companies and research institutions
Universities, national labs, and research institutes also sponsor H-1B visas for ML scientists. These employers often have cap-exempt status, avoiding the annual lottery entirely.
Build a portfolio demonstrating real-world ML applications
Showcase projects involving deep learning, natural language processing, computer vision, or reinforcement learning. Concrete examples strengthen your specialty occupation case during the petition process.
Network through ML conferences and academic publications
Connect with potential sponsors at NeurIPS, ICML, or ICLR conferences. Co-authored papers with U.S. researchers can open doors to academic or industry positions.
Machine Learning Scientist jobs are hiring across the US. Find yours.
Find Machine Learning Scientist JobsFrequently Asked Questions
Do machine learning scientists qualify for H-1B specialty occupation requirements?
Yes, machine learning scientist roles consistently meet H-1B specialty occupation criteria. The position requires advanced knowledge in mathematics, statistics, computer science, and specialized ML frameworks. Most employers require at least a master's degree in a relevant field, and the role involves complex algorithm development that clearly demonstrates specialized expertise.
What degree fields qualify for machine learning scientist visa petitions?
Computer science, mathematics, statistics, electrical engineering, physics, and data science degrees typically qualify. The key is demonstrating how your coursework relates to machine learning fundamentals like linear algebra, probability theory, algorithms, and programming. A PhD in any of these fields significantly strengthens your petition case.
Are machine learning scientists eligible for cap-exempt H-1B positions?
Yes, if working for universities, affiliated research institutions, or nonprofit research organizations. Many academic ML positions are cap-exempt, meaning no lottery participation required. Private companies are generally cap-subject, but some have university affiliations that may qualify for exemptions.
How do ML scientists demonstrate extraordinary ability for O-1 visas?
O-1 criteria include published research papers, conference presentations, peer review activities, high-impact citations, and recognition awards. Leading ML research projects, developing novel algorithms, or contributing to widely-used frameworks can also demonstrate extraordinary ability in the field.
Can machine learning scientists transition from F-1 student status to work visas?
Yes, through OPT and STEM OPT extensions totaling up to 36 months. This provides time to find sponsoring employers and participate in H-1B lotteries. Many ML PhD students also transition directly to cap-exempt academic positions or receive National Interest Waiver green cards based on their research contributions.
How to find Machine Learning Scientist jobs with visa sponsorship?
To find Machine Learning Scientist positions with visa sponsorship, use Migrate Mate, which specializes in connecting international talent with sponsoring employers. Focus on tech companies, research institutions, and AI startups that commonly sponsor H-1B, O-1, or EB-2 visas for ML roles. These employers actively seek candidates with expertise in deep learning, neural networks, and data science to drive their AI initiatives.
What is the prevailing wage requirement for sponsored Machine Learning Scientist 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.
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