Science & Research OPT Jobs in New York
New York is one of the strongest states for science and research F-1 OPT sponsorship, with major employers spanning pharmaceutical giants in Manhattan, biotech firms along the Hudson Valley corridor, and research institutions including Columbia University, Rockefeller University, and Memorial Sloan Kettering. OPT-eligible students in biology, chemistry, public health, and related fields will find active hiring across the state.
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Get Access To All JobsAbout Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About The Role
We're looking for a Research Scientist who has done hands-on research on large models (pretraining, fine-tuning, RL, evals, or agents scaffolds) and wants to focus on measuring and understanding recursive-self-improvement. You know what the model-development loop looks like from the inside: which signals matter and where the real bottlenecks are. On this team you'll use that judgment to decide what's worth measuring, design the evaluations and models that measure it, and interpret what the results mean for how fast this is moving. We're hiring at both junior and senior levels. Senior researchers should be comfortable doing hands-on technical work alongside setting research direction.
Responsibilities
- Identify the signals that track AI R&D acceleration and design the evaluations that measure them
- Build quantitative models of capability growth and self-improvement dynamics, grounded in evaluation and telemetry data
- Run experiments and evals to test hypotheses about automation and capability
- Make opinionated research bets and own the outcome
- Write graded assessments of what our measurements show, for internal decision-makers and public reporting
- Collaborate with pretraining, RL, economic research, and policy teams
You may be a good fit if you
- Have done hands-on research on large language models: pretraining, fine-tuning, RL, evals, or agent systems
- Have strong quantitative instincts, are comfortable with quantitative modeling and reasoning
- Have experience in forecasting, may have published AI forecasting scenarios
- Can design an evaluation from a vague question and defend the methodology
- Write clearly and calibrate: state confidence, name what would change your conclusion
- Are motivated by impact: comfortable with work whose output is graded assessments and system-card sections more often than papers
- Care about AI safety and think carefully about where rapid capability growth leads
Strong candidates may also have
- Trained or RL'd frontier models hands-on
- Experience with scaling laws, capability forecasting, or emergent-capability studies
- A physics, applied-math, or similarly quantitative background that moved into ML
- Written a system card section, capability report, or methodology document that others cite
- Experience supervising and correcting AI-written code
Some examples of our work
- Anthropic ECI: our adaptation of Epoch Capabilities Index published in all recent system cards to measure capability acceleration
- AI R&D capability assessments in the Claude system cards
- When AI Builds Itself: all data in the article comes from our team
Compensation
The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
- Annual Salary: $350,000—$850,000 USD
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How We're Different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About The Role
We're looking for a Research Scientist who has done hands-on research on large models (pretraining, fine-tuning, RL, evals, or agents scaffolds) and wants to focus on measuring and understanding recursive-self-improvement. You know what the model-development loop looks like from the inside: which signals matter and where the real bottlenecks are. On this team you'll use that judgment to decide what's worth measuring, design the evaluations and models that measure it, and interpret what the results mean for how fast this is moving. We're hiring at both junior and senior levels. Senior researchers should be comfortable doing hands-on technical work alongside setting research direction.
Responsibilities
- Identify the signals that track AI R&D acceleration and design the evaluations that measure them
- Build quantitative models of capability growth and self-improvement dynamics, grounded in evaluation and telemetry data
- Run experiments and evals to test hypotheses about automation and capability
- Make opinionated research bets and own the outcome
- Write graded assessments of what our measurements show, for internal decision-makers and public reporting
- Collaborate with pretraining, RL, economic research, and policy teams
You may be a good fit if you
- Have done hands-on research on large language models: pretraining, fine-tuning, RL, evals, or agent systems
- Have strong quantitative instincts, are comfortable with quantitative modeling and reasoning
- Have experience in forecasting, may have published AI forecasting scenarios
- Can design an evaluation from a vague question and defend the methodology
- Write clearly and calibrate: state confidence, name what would change your conclusion
- Are motivated by impact: comfortable with work whose output is graded assessments and system-card sections more often than papers
- Care about AI safety and think carefully about where rapid capability growth leads
Strong candidates may also have
- Trained or RL'd frontier models hands-on
- Experience with scaling laws, capability forecasting, or emergent-capability studies
- A physics, applied-math, or similarly quantitative background that moved into ML
- Written a system card section, capability report, or methodology document that others cite
- Experience supervising and correcting AI-written code
Some examples of our work
- Anthropic ECI: our adaptation of Epoch Capabilities Index published in all recent system cards to measure capability acceleration
- AI R&D capability assessments in the Claude system cards
- When AI Builds Itself: all data in the article comes from our team
Compensation
The annual compensation range for this role is listed below. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
- Annual Salary: $350,000—$850,000 USD
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
Your safety matters to us.
To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How We're Different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
OPT Science & Research Job Roles in New York
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Search Science & Research Jobs in New YorkScience & Research OPT Sponsorship Jobs in New York: Frequently Asked Questions
Which science and research companies sponsor F-1 OPT visas in New York?
New York hosts a range of science and research employers with established OPT sponsorship track records. Pfizer, Bristol Myers Squibb, and Regeneron operate significant research functions in the state, as do major academic medical centers like Weill Cornell Medicine and New York-Presbyterian. Research-focused nonprofits and government laboratories, including Brookhaven National Laboratory on Long Island, also regularly hire OPT-authorized candidates in scientific roles.
Which cities in New York have the most science and research F-1 OPT sponsorship jobs?
New York City, particularly Manhattan and the emerging life sciences corridor around East River Science Park in Kips Bay, concentrates the largest share of science and research OPT roles in the state. The Hudson Valley region, including Tarrytown and Pearl River, hosts significant pharmaceutical and biotech operations. Long Island, anchored by Brookhaven National Laboratory and Cold Spring Harbor Laboratory, is another active cluster for research-oriented OPT candidates.
What types of science and research roles typically qualify for F-1 OPT sponsorship?
Roles that directly apply a student's field of study qualify for standard 12-month OPT, while STEM-designated programs extend eligibility to 24 additional months. In science and research, qualifying positions commonly include research associate, lab technician, computational biologist, data scientist in life sciences, clinical research coordinator, and environmental scientist. The role must be directly related to the degree field, so a chemistry graduate working in a biology lab may need to verify alignment with their program.
How do I find science & research F-1 OPT sponsorship jobs in New York?
Migrate Mate is designed specifically for international students and filters science and research jobs in New York by visa type, including F-1 OPT, so you are not sorting through listings from employers who cannot sponsor. Beyond Migrate Mate, your university's international office and career center often maintain relationships with New York employers experienced in OPT hiring, and on-campus research positions can be a direct entry point into the state's science and research employment network.
Are there any state-specific or industry-specific considerations for F-1 OPT sponsorship in New York's science and research sector?
New York State has invested in life sciences through initiatives like the Life Science Initiative, which has attracted employers more familiar with sponsoring international talent. However, many smaller biotech startups in the state may lack experience navigating OPT authorization paperwork, so candidates should confirm employer familiarity with E-Verify and OPT employment authorization requirements early in the hiring process. For STEM OPT extensions, the employer must be enrolled in E-Verify, which is a federal requirement regardless of state.