Machine Learning Scientist Visa Sponsorship Jobs in New York
New York is one of the top states for machine learning scientist roles, with major employers including Google, Meta, IBM, Bloomberg, and a dense cluster of fintech and healthtech firms in Manhattan. Research institutions like NYU and Columbia also drive demand. Most roles are concentrated in New York City, with a growing presence in Brooklyn's tech corridor.
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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
Machine Learning Scientist Job Roles in New York
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Search Machine Learning Scientist Jobs in New YorkMachine Learning Scientist Jobs in New York: Frequently Asked Questions
Which companies sponsor visas for machine learning scientists in New York?
Large technology and financial firms are the most consistent sponsors. Google, Meta, Amazon, IBM, and Microsoft all have significant New York operations and established visa sponsorship programs for machine learning scientists. Bloomberg, Two Sigma, and other fintech firms also regularly sponsor H-1B petitions for these roles. Healthtech companies and research-focused organizations like Memorial Sloan Kettering have become active sponsors as well.
Which visa types are most common for machine learning scientist roles in New York?
The H-1B is the most common visa for machine learning scientists in New York, given that the role clearly meets the specialty occupation standard requiring a bachelor's degree or higher in computer science, statistics, or a related field. Candidates with extraordinary recognition in the field may qualify for the O-1A. Those already holding an advanced degree from a U.S. university may also have employer-sponsored EB-2 or EB-3 green card pathways initiated alongside their nonimmigrant status.
How to find machine learning scientist visa sponsorship jobs in New York?
Migrate Mate is built specifically for international candidates seeking visa sponsorship and lets you filter machine learning scientist roles by state, so you can focus directly on New York employers who are open to sponsoring. Because sponsorship intent isn't always stated in a job listing, Migrate Mate surfaces roles from companies with a documented history of filing H-1B petitions for machine learning and AI positions, saving significant research time.
Which cities in New York have the most machine learning scientist sponsorship jobs?
New York City accounts for the overwhelming majority of machine learning scientist sponsorship activity in the state. Manhattan, particularly Midtown and the Flatiron District, is home to most of the large tech and finance employers. Brooklyn's DUMBO and Industry City areas have a growing concentration of AI startups and research labs. Buffalo and Albany have a smaller but emerging presence, driven by state-funded technology initiatives and university research partnerships.
Are there state-specific factors that affect visa sponsorship for machine learning scientists in New York?
New York employers filing Labor Condition Applications must pay the prevailing wage for the specific metropolitan area where the work is performed, and New York City prevailing wages for machine learning scientists are among the highest in the country. The dense concentration of H-1B-dependent employers in finance and tech means competition for sponsorship slots is real, and companies in these sectors tend to initiate the process well before the April H-1B filing window. NYU, Columbia, and Cornell Tech produce a significant pipeline of candidates, which shapes how employers recruit.
What is the prevailing wage for sponsored machine learning scientist jobs in New York?
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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