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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SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. We’re building the future of identity verification in the United States, replacing a clunky, ineffective, and expensive status quo with solutions that are 10x faster, smarter, and more accurate. We’ve seen tremendous traction and are growing extremely quickly. Our real-time APIs have helped verify hundreds of millions of identities, starting with financial services and rapidly expanding into new markets. SentiLink is backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin. We’ve earned recognition from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, American Banker, LendIt, and have been named to the Forbes Fintech 50 list every year since 2023. Last but not least, we’ve even made history - we were the first company to go live with the eCBSV and testified before the United States House of Representatives on the future of identity. SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We operate as a digital-first company with strong collaboration across the U.S. and India. We maintain physical offices in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India. If you’re located near one of these offices, we would love for you to spend time in the office regularly. Some roles are hybrid or in-office by design. For example, our engineering team in India works primarily from our Gurugram office.
ROLE
As a Senior Applied ML Scientist at SentiLink, you will build our core products: models that identify fraudsters and also advance our growing suite of products in financial risk. As an experienced researcher, you will be relied upon to be technically capable and the definitive owner of your respective domain. You will often work on projects with high visibility and impact that require deep domain understanding, critical thinking, and strong technical abilities. You will work with teams across the company to research new types of fraud, develop new products, and provide analysis to drive sales and marketing. This is a full-stack data science role, involving model development, analysis, and writing production code. You should be interested in having end-to-end ownership and a fast-moving environment where deep domain understanding drives development and unusual insights drive our competitive advantage rather than optimization of new machine learning methodologies.
We Have Open Roles On Multiple Teams Including
- Emerging Products - focuses on 0-to-1 development of new offerings brought to market
- Application Fraud - analyzes the foundational elements of consumer financial applications to detect all forms of fraud
- Identity - resolves identities across massive, often conflicting data sources (both digital and physical) and generates risk models from limited information
Technologies: Python 3, PostgreSQL, and AWS infrastructure (EC2, S3, RDS, Redshift, etc.)
Responsibilities
- Develop and maintain SentiLink’s fraud detection models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring.
- Build foundational modeling to drive SentiLink’s expanding suite of Fraud and Financial Risk products.
- Research new types of fraud and develop new SentiLink products around identity verification.
- Achieve success by researching / developing through iteration, integration of new data sources, and inventive feature engineering.
- Write production-ready code that can be relied on for real-time decision making by our partners.
- Design, perform, and present analyses that will inform data acquisition, product development, risk operations priorities, marketing, and sales efforts.
- Work with engineering, risk operations, and data acquisitions to access necessary data, maintain data quality, and support data access.
REQUIREMENTS
- 4+ years relevant work experience & relevant PhD or 6+ years & relevant Masters
- Proven track record of solving complex / high profile business problems with DS / ML solutions
- Experience in communicating outcomes / progress to senior management / stakeholders
- Very strong in “end to end” DS development: Planning, fleshing out success criteria / metrics, getting buy-in, developing the solution, delivering the solution (prod / deck / strategy doc / etc)
- Strong practical ML / Stats knowledge, i.e. can easily employ the suite of standard ML / stats tools to quickly scope out solutions, and double down where needed. Experience with SOTA ML solutions is a plus
- Interest in developing deep domain expertise for product-focused work: a background in fraud is not required, but willingness to learn is
- Experience writing production code and tests
- Detail oriented and thoughtful - someone we can rely on to make business-changing decisions
- Bonus for familiarity with: identity solutions, fintech, or adjacent industries
- Experience working at a startup strongly preferred
- Thrive in a fast-paced environment characterized by the need to solve extremely varied, high impact, open-ended problems.
- Candidates must be legally authorized to work in the United States and must live in the United States
SALARY RANGE
- $200,000/year - $240,000/year + equity + benefits
PERKS
- Employer paid group health insurance for you and your dependents
- 401(k) plan with employer match (or equivalent for non US-based roles)
- Flexible paid time off
- Regular company-wide in-person events
- Home office stipend, and more!
CORPORATE VALUES
- Follow Through
- Deep Understanding
- Whatever It Takes
- Do Something Smart
INTRODUCTION
SentiLink provides innovative identity and risk solutions, empowering institutions and individuals to transact with confidence. We’re building the future of identity verification in the United States, replacing a clunky, ineffective, and expensive status quo with solutions that are 10x faster, smarter, and more accurate. We’ve seen tremendous traction and are growing extremely quickly. Our real-time APIs have helped verify hundreds of millions of identities, starting with financial services and rapidly expanding into new markets. SentiLink is backed by world-class investors including Craft Ventures, Andreessen Horowitz, NYCA, and Max Levchin. We’ve earned recognition from TechCrunch, CNBC, Bloomberg, Forbes, Business Insider, PYMNTS, American Banker, LendIt, and have been named to the Forbes Fintech 50 list every year since 2023. Last but not least, we’ve even made history - we were the first company to go live with the eCBSV and testified before the United States House of Representatives on the future of identity. SentiLink supports a variety of ways to work, ranging from fully remote to in-office. We operate as a digital-first company with strong collaboration across the U.S. and India. We maintain physical offices in Austin, San Francisco, New York City, Seattle, Los Angeles, and Chicago in the U.S., and in Gurugram (Delhi) and Bengaluru in India. If you’re located near one of these offices, we would love for you to spend time in the office regularly. Some roles are hybrid or in-office by design. For example, our engineering team in India works primarily from our Gurugram office.
ROLE
As a Senior Applied ML Scientist at SentiLink, you will build our core products: models that identify fraudsters and also advance our growing suite of products in financial risk. As an experienced researcher, you will be relied upon to be technically capable and the definitive owner of your respective domain. You will often work on projects with high visibility and impact that require deep domain understanding, critical thinking, and strong technical abilities. You will work with teams across the company to research new types of fraud, develop new products, and provide analysis to drive sales and marketing. This is a full-stack data science role, involving model development, analysis, and writing production code. You should be interested in having end-to-end ownership and a fast-moving environment where deep domain understanding drives development and unusual insights drive our competitive advantage rather than optimization of new machine learning methodologies.
We Have Open Roles On Multiple Teams Including
- Emerging Products - focuses on 0-to-1 development of new offerings brought to market
- Application Fraud - analyzes the foundational elements of consumer financial applications to detect all forms of fraud
- Identity - resolves identities across massive, often conflicting data sources (both digital and physical) and generates risk models from limited information
Technologies: Python 3, PostgreSQL, and AWS infrastructure (EC2, S3, RDS, Redshift, etc.)
Responsibilities
- Develop and maintain SentiLink’s fraud detection models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring.
- Build foundational modeling to drive SentiLink’s expanding suite of Fraud and Financial Risk products.
- Research new types of fraud and develop new SentiLink products around identity verification.
- Achieve success by researching / developing through iteration, integration of new data sources, and inventive feature engineering.
- Write production-ready code that can be relied on for real-time decision making by our partners.
- Design, perform, and present analyses that will inform data acquisition, product development, risk operations priorities, marketing, and sales efforts.
- Work with engineering, risk operations, and data acquisitions to access necessary data, maintain data quality, and support data access.
REQUIREMENTS
- 4+ years relevant work experience & relevant PhD or 6+ years & relevant Masters
- Proven track record of solving complex / high profile business problems with DS / ML solutions
- Experience in communicating outcomes / progress to senior management / stakeholders
- Very strong in “end to end” DS development: Planning, fleshing out success criteria / metrics, getting buy-in, developing the solution, delivering the solution (prod / deck / strategy doc / etc)
- Strong practical ML / Stats knowledge, i.e. can easily employ the suite of standard ML / stats tools to quickly scope out solutions, and double down where needed. Experience with SOTA ML solutions is a plus
- Interest in developing deep domain expertise for product-focused work: a background in fraud is not required, but willingness to learn is
- Experience writing production code and tests
- Detail oriented and thoughtful - someone we can rely on to make business-changing decisions
- Bonus for familiarity with: identity solutions, fintech, or adjacent industries
- Experience working at a startup strongly preferred
- Thrive in a fast-paced environment characterized by the need to solve extremely varied, high impact, open-ended problems.
- Candidates must be legally authorized to work in the United States and must live in the United States
SALARY RANGE
- $200,000/year - $240,000/year + equity + benefits
PERKS
- Employer paid group health insurance for you and your dependents
- 401(k) plan with employer match (or equivalent for non US-based roles)
- Flexible paid time off
- Regular company-wide in-person events
- Home office stipend, and more!
CORPORATE VALUES
- Follow Through
- Deep Understanding
- Whatever It Takes
- Do Something Smart
How to Get 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.
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Get Access To All 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.
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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