H-1B Visa Applied Scientist Jobs
Applied Scientist roles sit squarely within H-1B visa specialty occupation requirements, with most positions requiring a master's or PhD in computer science, statistics, or a related field. Large tech and research employers file H-1B petitions regularly for this title, making it one of the more sponsorship-accessible roles in data and machine learning.
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Interested in setting the scientific vision for how every product at Amazon is understood, identified, and connected, with the opportunity to impact every Amazon customer and every selling partner?
The Items and Relationships Platform is the foundation that establishes what every product in Amazon’s catalog is and how products relate to one another. We are rebuilding the platform to establish identity and relationships from meaning and context, using multimodal large language models and generative AI. This is a foundational problem: understanding products deeply enough to identify them, relate them, and keep the catalog trustworthy as it scales to the full breadth of Amazon’s global contribution traffic.
A Principal Applied Scientist on the Items and Relationships Platform owns the science direction for product identity and product relationships. It spans how contributions are resolved into a committed product identity, how products are connected into structural relationships (variations, multipacks, newer versions, lines of products, bundles), how confident those decisions are, and how their quality is measured. You will own the strategy for multimodal understanding, representation learning, relationship inference, calibration, and evaluation, so that science capability compounds across identity and relationships rather than being built one use case at a time.
This role lives at the intersection of research and production. Product identity and relationships are fundamentally an entity resolution problem: deciding what is the same product, and how different products relate, across diverse sources, languages, and formats. You will make the hard modeling calls on where sameness ends and relatedness begins, how models express and calibrate confidence, and how the platform measures quality when there is no external ground truth.
Successful candidates are passionate about translating ambiguous business goals into a coherent science roadmap that enables many businesses at once. You are comfortable being the final scientific arbiter on hard cross-team decisions, and working alongside top-notch applied scientists and software engineers to turn advanced research into production systems.
Key job responsibilities
As a Principal Applied Scientist on the Items and Relationships Platform, you will:
-
Own the science direction for product identity: define how products are semantically understood, resolved, and committed as coherent identities, navigating the precision/recall and friction/selection trade-offs inherent in every decision
-
Build representations that decide both sameness and typed relatedness, and drive relationship inference from semantic identity rather than one pipeline per relationship type
-
Own structural relationship science across variations, multipacks and base products, newer versions, lines of products, and bundles, and discover new relationship types from the gap between defined policy and what identity reveals
-
Own calibration and evaluation science: define how models emit calibrated confidence, and build the LLM judge methodology and Catalog Identity Quality metric that measure identity and relationship quality at catalog scale
-
Partner with Principal Engineers on cost-aware modeling (cascades, distillation, routing) and close the loop from production signals and corrections back into training
-
Set science direction partnering with ACCS Applied Science teams, mentoring senior and principal-track scientists, and driving the documentation and publication of scientific innovation
A day in the life
On a typical day, you move between setting science direction and going deep on hard problems: reviewing a multimodal identity model or a relationship inference experiment with scientists, deciding how a borderline case (a multipack, a newer version, a near-identical variant) should be modeled, and pressure-testing whether a quality gain is real by examining the judge and its calibration. You also spend time zoomed out, shaping the longer-term science roadmap, aligning with Principal Engineers and partner teams on the identity and relationship signals they consume, and mentoring scientists as they take on the ambiguous, high-impact problems that define the platform’s future.
About the team
The Items and Relationships Platform advances state-of-the-art GenAI to deeply understand, uniquely identify, and meaningfully connect every product at Amazon scale. We build the canonical product identity, matching, and relationship systems that power Amazon’s universal catalog: eliminating duplicates, preventing abuse, keeping product families coherent, and integrating the world’s product data to power agentic shopping and trusted discovery for customers worldwide. We solve foundational challenges including schema-agnostic multimodal understanding, relationship inference, evaluation without ground truth, and efficient inference at reduced cost.
BASIC QUALIFICATIONS
- 5+ years of hands-on work in predictive modeling and analysis experience
- PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field
- Experience working in predictive modeling and analysis
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Experience programming in Java, C++, Python or related language
- Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment
PREFERRED QUALIFICATIONS
- 10+ years of relevant work in industry or academia experience
- Knowledge of problem solving, algorithm design and complexity analysis
- Experience creating novel algorithms and advancing the state of the art
- Have peer-reviewed scientific contributions in premier journals and conferences
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
Location: USA, WA, Seattle
Salary: 198,900.00 - 269,000.00 USD annually
DESCRIPTION
Interested in setting the scientific vision for how every product at Amazon is understood, identified, and connected, with the opportunity to impact every Amazon customer and every selling partner?
The Items and Relationships Platform is the foundation that establishes what every product in Amazon’s catalog is and how products relate to one another. We are rebuilding the platform to establish identity and relationships from meaning and context, using multimodal large language models and generative AI. This is a foundational problem: understanding products deeply enough to identify them, relate them, and keep the catalog trustworthy as it scales to the full breadth of Amazon’s global contribution traffic.
A Principal Applied Scientist on the Items and Relationships Platform owns the science direction for product identity and product relationships. It spans how contributions are resolved into a committed product identity, how products are connected into structural relationships (variations, multipacks, newer versions, lines of products, bundles), how confident those decisions are, and how their quality is measured. You will own the strategy for multimodal understanding, representation learning, relationship inference, calibration, and evaluation, so that science capability compounds across identity and relationships rather than being built one use case at a time.
This role lives at the intersection of research and production. Product identity and relationships are fundamentally an entity resolution problem: deciding what is the same product, and how different products relate, across diverse sources, languages, and formats. You will make the hard modeling calls on where sameness ends and relatedness begins, how models express and calibrate confidence, and how the platform measures quality when there is no external ground truth.
Successful candidates are passionate about translating ambiguous business goals into a coherent science roadmap that enables many businesses at once. You are comfortable being the final scientific arbiter on hard cross-team decisions, and working alongside top-notch applied scientists and software engineers to turn advanced research into production systems.
Key job responsibilities
As a Principal Applied Scientist on the Items and Relationships Platform, you will:
-
Own the science direction for product identity: define how products are semantically understood, resolved, and committed as coherent identities, navigating the precision/recall and friction/selection trade-offs inherent in every decision
-
Build representations that decide both sameness and typed relatedness, and drive relationship inference from semantic identity rather than one pipeline per relationship type
-
Own structural relationship science across variations, multipacks and base products, newer versions, lines of products, and bundles, and discover new relationship types from the gap between defined policy and what identity reveals
-
Own calibration and evaluation science: define how models emit calibrated confidence, and build the LLM judge methodology and Catalog Identity Quality metric that measure identity and relationship quality at catalog scale
-
Partner with Principal Engineers on cost-aware modeling (cascades, distillation, routing) and close the loop from production signals and corrections back into training
-
Set science direction partnering with ACCS Applied Science teams, mentoring senior and principal-track scientists, and driving the documentation and publication of scientific innovation
A day in the life
On a typical day, you move between setting science direction and going deep on hard problems: reviewing a multimodal identity model or a relationship inference experiment with scientists, deciding how a borderline case (a multipack, a newer version, a near-identical variant) should be modeled, and pressure-testing whether a quality gain is real by examining the judge and its calibration. You also spend time zoomed out, shaping the longer-term science roadmap, aligning with Principal Engineers and partner teams on the identity and relationship signals they consume, and mentoring scientists as they take on the ambiguous, high-impact problems that define the platform’s future.
About the team
The Items and Relationships Platform advances state-of-the-art GenAI to deeply understand, uniquely identify, and meaningfully connect every product at Amazon scale. We build the canonical product identity, matching, and relationship systems that power Amazon’s universal catalog: eliminating duplicates, preventing abuse, keeping product families coherent, and integrating the world’s product data to power agentic shopping and trusted discovery for customers worldwide. We solve foundational challenges including schema-agnostic multimodal understanding, relationship inference, evaluation without ground truth, and efficient inference at reduced cost.
BASIC QUALIFICATIONS
- 5+ years of hands-on work in predictive modeling and analysis experience
- PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field
- Experience working in predictive modeling and analysis
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Experience programming in Java, C++, Python or related language
- Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment
PREFERRED QUALIFICATIONS
- 10+ years of relevant work in industry or academia experience
- Knowledge of problem solving, algorithm design and complexity analysis
- Experience creating novel algorithms and advancing the state of the art
- Have peer-reviewed scientific contributions in premier journals and conferences
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
Location: USA, WA, Seattle
Salary: 198,900.00 - 269,000.00 USD annually
See all 942+ H-1B Visa Applied Scientist Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new H-1B Visa Applied Scientist Jobs.
Get Access To All JobsTips for Finding H-1B Visa Sponsorship as an Applied Scientist
Align your degree to the SOC code
USCIS evaluates specialty occupation by matching your degree field to the role's SOC code. Applied Scientist roles often file under 15-2051 (Data Scientists) or 15-1221 (Computer and Information Research Scientists), so confirm your transcript language maps directly to whichever code your offer letter uses.
Check LCA filings before applying
Use Migrate Mate to filter Applied Scientist roles by employers with active H-1B LCA filing history. This surfaces companies that have already cleared DOL prevailing-wage certification for this title, cutting out employers who've never navigated the process.
Verify prevailing wage before negotiating
Run your target job's SOC code and work location through the OFLC Wage Search before your offer negotiation. Your employer's LCA must certify a wage at or above the DOL prevailing wage, so knowing the Level I through Level IV thresholds gives you a concrete floor to reference.
Request a cap-exempt employer when possible
Universities, nonprofit research organizations, and government research entities can file H-1B petitions outside the annual cap and lottery. Applied Scientist roles at national labs or research hospitals are often cap-exempt, which means you can start work on approval rather than waiting for an October 1 start date.
Prepare a strong body-of-work portfolio early
USCIS officers occasionally issue RFEs on Applied Scientist petitions questioning whether the role genuinely requires a specific degree. Published papers, patents, or documented model deployments tied to your academic specialty strengthen the specialty occupation argument before an RFE ever arrives.
Clarify filing responsibility before signing
Confirm in writing whether your employer uses in-house legal counsel or an outside immigration firm for H-1B filings, and ask who bears the I-129 filing fee. Employers are prohibited from passing certain USCIS fees to H-1B workers, so get the fee structure documented before your start date.
H-1B Visa Applied Scientist: Frequently Asked Questions
Does an Applied Scientist role qualify as a specialty occupation for H-1B purposes?
Yes. Applied Scientist positions typically require at least a bachelor's degree, and most employers require a master's or PhD in computer science, statistics, mathematics, or a closely related field. USCIS evaluates the specific degree requirement stated in the job description, so the offer letter and job duties need to clearly tie the role to a particular academic discipline rather than accepting any bachelor's degree.
Which employers sponsor H-1B visas for Applied Scientist roles?
Technology companies, cloud platform providers, financial services firms, and research-focused healthcare organizations are among the most active H-1B sponsors for Applied Scientist titles. You can search Migrate Mate to filter Applied Scientist openings by employers with verified H-1B LCA filing history, so you're targeting companies that have already demonstrated they sponsor this specific role type.
How does the H-1B lottery affect my timeline as an Applied Scientist?
If your target employer is cap-subject, USCIS opens H-1B registration in March and selects registrations by lottery. Selected petitions can begin October 1 of that fiscal year. Cap-exempt employers, including universities and qualifying nonprofit research organizations, can file at any time, which is worth factoring in when you're evaluating Applied Scientist opportunities.
What SOC code is typically used for Applied Scientist H-1B filings?
Most Applied Scientist petitions file under 15-2051 (Data Scientists) or 15-1221 (Computer and Information Research Scientists), depending on whether the role is primarily modeling and analysis or foundational research. The SOC code determines the DOL prevailing wage level your employer must certify on the LCA, so it directly affects your minimum compensation floor. You can cross-reference the O*NET profile for each code to see which best matches your actual duties.
Can I transfer my H-1B to a new Applied Scientist role at a different employer?
Yes. H-1B portability under AC21 lets you change employers once your petition has been pending for at least 180 days and you're moving to a same or similar occupational classification. Your new employer files an H-1B transfer petition, and you can start work as soon as USCIS receives it, without waiting for approval. Confirm with your new employer that the transfer petition will be filed before you leave your current role.