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Sr. Applied Scientist, Foundation Model Build, WW Sustainability
Job Location:
Job Location:
Seattle, OR - USA
Yearly Salary:
USD 167100 - 226100
Yearly Salary:
Posted:
29 September 2026 (4 days ago)
Posted:
Application Deadline:
2 October 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Build AI systems that help Amazon make better sustainability decisions at global scale. Our research questions require more than applying an existing model: they require new scientific methods trustworthy data foundations and a path from research hypothesis to production deployment.
Sustainability Science and Innovation (SSI) is Amazons applied research hub for environmental impact. We bring together applied scientists environmental scientists economists and engineers to develop and scale solutions across carbon water waste climate risk and responsible supply chainsfrom early hypothesis to production deployment at Amazon scale.
SSI is seeking a Senior Applied Scientist to own a research agenda at the intersection of artificial intelligence data and sustainability. The role will define the science roadmap formulate and test hypotheses establish evaluation standards and lead solutions from early experimentation through production deployment. Working closely with economists environmental scientists engineers and product leaders the Senior Applied Scientist will determine which scientific and technical approaches can produce decision-ready results at Amazon scale.
The work may include large language models multimodal models retrieval-augmented generation foundation-model adaptation and other modern machine-learning methods selected according to the scientific problem rather than applied as ends in themselves. The role will also define how strategic models and datasets are discovered evaluated ingested harmonized governed and maintained because trustworthy AI depends on traceable evidence stable data contracts and reproducible evaluation. Applications may include product-level carbon estimation climate-risk monitoring and responsible-supply-chain assessment.
This role is distinctive because Amazons operational scale creates scientific problems that few organizations can study with unique access to global-scale sustainability data. Youll leverage this unique access to establish scientific methods governance models and evaluation standards that can scale across multiple programs. This role shapes not just what problems we solve but how we solve them rigorously setting a template for AI-driven sustainability science across Amazons global operations.
Candidates do not need prior expertise in sustainability or climate science. The role requires a hands-on scientific leader who can develop rigorous AI and machine-learning methods work effectively across disciplines and translate uncertain research questions into measurable production-ready solutions.
Key job responsibilities
Own the research agenda and multi-year science roadmap for AI-enabled sustainability solutions.
Develop and evaluate modern AI and machine-learning methods including foundation models multimodal models retrieval-augmented generation and model adaptation.
Establish ex ante evaluation criteria benchmarks and launch thresholds that distinguish promising prototypes from production-ready methods.
Lead the full scientific lifecycle from problem formulation and experimentation through production deployment and post-launch measurement.
Define the architecture and governance required to make strategic models and datasets discoverable traceable reproducible and reusable.
Influence senior science engineering product and sustainability stakeholders across organizational boundaries.
Mentor scientists and raise the scientific standard through technical reviews publications and reusable methods.
About the team
Diverse Experiences:
World Wide Sustainability values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.
Inclusive Team Culture:
Its in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences including our Conversations on Race and Ethnicity (CORE) and AmazeCon (inclusive diversity) conferences inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth:
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance:
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home theres nothing we cant achieve.
- 3 years of building machine learning models for business application experience
- PhD or Masters degree and 6 years of applied research experience
- Experience programming in Java C Python or related language
- Experience with neural deep learning methods and machine learning
- Experience with modeling tools such as R scikit-learn Spark MLLib MxNet Tensorflow numpy scipy etc.
- Experience with large scale distributed systems such as Hadoop Spark etc.
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 for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Sustainability Science and Innovation (SSI) is Amazons applied research hub for environmental impact. We bring together applied scientists environmental scientists economists and engineers to develop and scale solutions across carbon water waste climate risk and responsible supply chainsfrom early hypothesis to production deployment at Amazon scale.
SSI is seeking a Senior Applied Scientist to own a research agenda at the intersection of artificial intelligence data and sustainability. The role will define the science roadmap formulate and test hypotheses establish evaluation standards and lead solutions from early experimentation through production deployment. Working closely with economists environmental scientists engineers and product leaders the Senior Applied Scientist will determine which scientific and technical approaches can produce decision-ready results at Amazon scale.
The work may include large language models multimodal models retrieval-augmented generation foundation-model adaptation and other modern machine-learning methods selected according to the scientific problem rather than applied as ends in themselves. The role will also define how strategic models and datasets are discovered evaluated ingested harmonized governed and maintained because trustworthy AI depends on traceable evidence stable data contracts and reproducible evaluation. Applications may include product-level carbon estimation climate-risk monitoring and responsible-supply-chain assessment.
This role is distinctive because Amazons operational scale creates scientific problems that few organizations can study with unique access to global-scale sustainability data. Youll leverage this unique access to establish scientific methods governance models and evaluation standards that can scale across multiple programs. This role shapes not just what problems we solve but how we solve them rigorously setting a template for AI-driven sustainability science across Amazons global operations.
Candidates do not need prior expertise in sustainability or climate science. The role requires a hands-on scientific leader who can develop rigorous AI and machine-learning methods work effectively across disciplines and translate uncertain research questions into measurable production-ready solutions.
Key job responsibilities
Own the research agenda and multi-year science roadmap for AI-enabled sustainability solutions.
Develop and evaluate modern AI and machine-learning methods including foundation models multimodal models retrieval-augmented generation and model adaptation.
Establish ex ante evaluation criteria benchmarks and launch thresholds that distinguish promising prototypes from production-ready methods.
Lead the full scientific lifecycle from problem formulation and experimentation through production deployment and post-launch measurement.
Define the architecture and governance required to make strategic models and datasets discoverable traceable reproducible and reusable.
Influence senior science engineering product and sustainability stakeholders across organizational boundaries.
Mentor scientists and raise the scientific standard through technical reviews publications and reusable methods.
About the team
Diverse Experiences:
World Wide Sustainability values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.
Inclusive Team Culture:
Its in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences including our Conversations on Race and Ethnicity (CORE) and AmazeCon (inclusive diversity) conferences inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth:
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance:
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home theres nothing we cant achieve.
- 3 years of building machine learning models for business application experience
- PhD or Masters degree and 6 years of applied research experience
- Experience programming in Java C Python or related language
- Experience with neural deep learning methods and machine learning
- Experience with modeling tools such as R scikit-learn Spark MLLib MxNet Tensorflow numpy scipy etc.
- Experience with large scale distributed systems such as Hadoop Spark etc.
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 for more information. If the country/region youre applying in isnt 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 WA Seattle - 167100.00 - 226100.00 USD annually
Required Experience:
Senior IC
About Company
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