H-1B1 Singapore Visa Applied Scientist Jobs
Applied Scientist jobs with H-1B1 Singapore visa sponsorship give Singaporean nationals a direct path to U.S. research and machine learning roles without lottery risk. The H-1B1 cap of 5,400 visas rarely fills, and consulate processing in Singapore means no USCIS petition wait before you start.
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At Amazon Selection and Catalog Systems (ASCS), our mission is to power the online buying experience for customers worldwide so they can find, discover, and buy any product they want. We innovate on behalf of our customers to ensure uniqueness and consistency of product identity and to infer relationships between products in Amazon Catalog to drive the selection gateway for the search and browse experiences on the website. We're solving a fundamental AI challenge: establishing product relevant information at unprecedented scale with Frontier Models and Agents. The scale is staggering: billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity ranging from electronics to groceries to digital content.
The research challenges are immense. GenAI and VLMs hold transformative promise for catalog understanding, but we operate where traditional methods fail: ambiguous problem spaces, incomplete and noisy data, inherent uncertainty, reasoning across both images and textual data, and explaining decisions at scale. Enriching product information requires sophisticated models that reason across text, images, and structured data, all while maintaining accuracy and trust for high-stakes business decisions affecting millions of customers daily.
Amazon's Catalog System Services Science team is looking for an innovative and customer-focused applied scientist to help us make the world's best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services. You will pioneer advanced GenAI solutions that power next-generation agentic shopping experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your algorithmic ideas at scale, across millions of customers.
Key job responsibilities
- Formulate novel research problems at the intersection of GenAI, multimodal learning, and large-scale information retrieval. In essence, translating ambiguous business challenges into tractable scientific frameworks
- Design and implement leading models leveraging frontier models, and agentic architectures to enrich catalog information at billion-product scale
- Pioneer explainable AI methodologies that balance model performance with scalability requirements for production systems impacting millions of daily customer decisions
- Own end-to-end ML pipelines from research ideation to production deployment, processing petabytes of multimodal data with rigorous evaluation frameworks
- Represent the team in the broader science community - publishing findings, delivering tech talks, and staying at the forefront of GenAI, VLM, and agentic system research
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- 2+ years of building machine learning models or developing algorithms for business application experience
- Prior experience in the domains of LLMs, or large-scale deep learning systems
PREFERRED QUALIFICATIONS
- Publications in top-tier venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, EMNLP, ACL, NAACL, COLING, KDD, SIGMOD, WWW, AAAI, or similar
- Experience with multimodal LLMs, including hands-on post training techniques
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
COMPENSATION
- Salary Range: $142,800.00 - $193,200.00 USD annually
DESCRIPTION
At Amazon Selection and Catalog Systems (ASCS), our mission is to power the online buying experience for customers worldwide so they can find, discover, and buy any product they want. We innovate on behalf of our customers to ensure uniqueness and consistency of product identity and to infer relationships between products in Amazon Catalog to drive the selection gateway for the search and browse experiences on the website. We're solving a fundamental AI challenge: establishing product relevant information at unprecedented scale with Frontier Models and Agents. The scale is staggering: billions of products, petabytes of multimodal data, millions of sellers, dozens of languages, and infinite product diversity ranging from electronics to groceries to digital content.
The research challenges are immense. GenAI and VLMs hold transformative promise for catalog understanding, but we operate where traditional methods fail: ambiguous problem spaces, incomplete and noisy data, inherent uncertainty, reasoning across both images and textual data, and explaining decisions at scale. Enriching product information requires sophisticated models that reason across text, images, and structured data, all while maintaining accuracy and trust for high-stakes business decisions affecting millions of customers daily.
Amazon's Catalog System Services Science team is looking for an innovative and customer-focused applied scientist to help us make the world's best product catalog even better. In this role, you will partner with technology and business leaders to build new state-of-the-art algorithms, models, and services. You will pioneer advanced GenAI solutions that power next-generation agentic shopping experiences, working in a collaborative environment where you can experiment with massive data from the world's largest product catalog, tackle problems at the frontier of AI research, rapidly implement and deploy your algorithmic ideas at scale, across millions of customers.
Key job responsibilities
- Formulate novel research problems at the intersection of GenAI, multimodal learning, and large-scale information retrieval. In essence, translating ambiguous business challenges into tractable scientific frameworks
- Design and implement leading models leveraging frontier models, and agentic architectures to enrich catalog information at billion-product scale
- Pioneer explainable AI methodologies that balance model performance with scalability requirements for production systems impacting millions of daily customer decisions
- Own end-to-end ML pipelines from research ideation to production deployment, processing petabytes of multimodal data with rigorous evaluation frameworks
- Represent the team in the broader science community - publishing findings, delivering tech talks, and staying at the forefront of GenAI, VLM, and agentic system research
BASIC QUALIFICATIONS
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- 2+ years of building machine learning models or developing algorithms for business application experience
- Prior experience in the domains of LLMs, or large-scale deep learning systems
PREFERRED QUALIFICATIONS
- Publications in top-tier venues such as NeurIPS, ICML, ICLR, CVPR, ICCV, EMNLP, ACL, NAACL, COLING, KDD, SIGMOD, WWW, AAAI, or similar
- Experience with multimodal LLMs, including hands-on post training techniques
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
COMPENSATION
- Salary Range: $142,800.00 - $193,200.00 USD annually
See all 531+ H-1B1 Singapore Visa Applied Scientist Jobs
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Get Access To All JobsTips for Finding Visa Sponsorship as an Applied Scientist
Verify your degree field matches the role
H-1B1 visa requires a specialty occupation with a direct degree-to-job connection. For Applied Scientist roles, a degree in computer science, statistics, or a closely related quantitative field is expected. A general business or unrelated STEM degree can draw scrutiny at the consulate.
Check the prevailing wage before negotiating
Your employer must file an LCA certifying your offered wage meets the DOL prevailing wage for Applied Scientist in your work location. Run the OFLC Wage Search before your offer stage so you know the floor and can negotiate above it.
Target employers with active LCA filing history
Not every tech or research employer understands the H-1B1 visa process. Use Migrate Mate to filter Applied Scientist roles by employers who have filed H-1B1 visa or H-1B visa LCAs, so you're pursuing companies already set up to sponsor rather than educating HR from scratch.
Confirm your employer enrolls in E-Verify
E-Verify enrollment isn't required for all H-1B1 visa employers, but many large tech and federal contractor employers use it. Ask during the offer stage, since E-Verify status affects onboarding timelines and whether you'll face additional I-9 verification steps on day one.
Prepare your O*NET occupation classification early
Consular officers and employers reference the O*NET profile for Applied Scientist to confirm specialty occupation status. Pull the O*NET entry before your interview and reconcile your actual job duties against the listed tasks, since a poor match between your offer letter and the profile is a common source of additional documentation requests.
Request a short start-date window in your offer letter
H-1B1 visa consulate appointments in Singapore move faster than USCIS processing, but your visa is tied to the LCA start date. Negotiate a start date at least four to six weeks out to give your employer time to get LCA certification from DOL before your interview.
Frequently Asked Questions
Does an Applied Scientist role qualify as a specialty occupation for the H-1B1 Singapore visa?
Yes. Applied Scientist roles typically require at least a bachelor's degree in computer science, machine learning, statistics, or a directly related quantitative field, which meets the specialty occupation standard. Your employer confirms this in the Labor Condition Application filed with DOL before your consulate appointment. If your job duties include significant research, modeling, or algorithm development, the classification is straightforward.
How does the H-1B1 Singapore visa compare to H-1B for Applied Scientist positions?
The H-1B1 visa skips the annual lottery entirely, which is the single biggest practical difference for Singaporean nationals. H-1B has an 85,000-slot cap with a registration lottery that leaves many qualified candidates unselected. The H-1B1 has a separate 5,400-slot annual cap that historically goes unused, and your application is adjudicated at the U.S. Embassy in Singapore rather than through a months-long USCIS review. The tradeoff is that H-1B1 doesn't allow dual intent, so demonstrating nonimmigrant intent at the consulate matters.
How do I find Applied Scientist employers who will sponsor the H-1B1 Singapore visa?
Migrate Mate is built for this search. It filters Applied Scientist roles by employers with documented H-1B1 visa and H-1B LCA filing history, so you can identify companies that have already navigated visa sponsorship rather than approaching employers who have never done it. This saves significant time during a job search where the employer's willingness to file is as important as the role itself.
Can I switch Applied Scientist employers while on H-1B1 status in the United States?
Yes, but the H-1B1 visa is employer-specific, so your new employer must file a fresh LCA and you'll need a new visa stamp at the consulate before or shortly after switching. There's no portability provision like H-1B's AC21 rule, so plan the timing carefully. A gap between your old employer's end date and the new LCA certification can create a status issue if not managed closely.
What happens if the DOL prevailing wage for Applied Scientist is higher than my offer?
Your employer cannot file a compliant LCA unless the offered wage meets or exceeds the DOL prevailing wage for the Applied Scientist occupation in your specific work location. If the offer is below that threshold, the employer must either raise the salary or the sponsorship can't proceed. Run the OFLC Wage Search before finalizing your offer so both you and your employer know the wage floor in advance.