The Worldwide Sustainability (WWS) organization capitalizes on Amazon’s scale & speed to build a more resilient and sustainable company. We manage our social and environmental impacts globally, driving solutions that enable our customers, businesses, and the world around us to become more sustainable.
Sustainability Science and Innovation (SSI) is a multi-disciplinary team within the WW Sustainability organization that combines science, analytics, economics, statistics, machine learning, product development, and engineering expertise. We use this expertise and skills to identify, develop and evaluate the science and innovations necessary for Amazon, customers and partners to meet their long-term sustainability goals and commitments.
We are seeking an Applied Scientist to join our AI and Sustainability team, which builds machine learning and AI based tools and well-established solutions that support sustainability teams across Amazon throughout their sustainability journey, enabling Amazon to accelerate the use of AI and progress toward our Climate Pledge sustainability commitments.
As an Applied Scientist, you’ll be responsible for designing, implementing and deploying state of the art solutions, to build AI-based solutions (LLM models, agents, copilots, RAGs, etc.) at scale for our long-term sustainability and climate commitments. Some examples of the problems you will work on include web-scale document extraction and conversation as they relate to sustainability, generation of decision-grade environmental impact measurements for abatement planning, tracking and reasoning, generation of assurance-grade ESG reports, novel supplier risk assessment, automated claims and substantiation, identification and sortation of waste streams, measuring the environmental impact of generative AI across its life cycle and more. You will ensure AI-based experiences delivered by Amazon uphold our Climate Pledge sustainability commitments and develop data-driven foundational services that make sustainability more effective and efficient. You will collaborate with a diverse set of sustainability scientists, subject matter experts, engineers, as well as internal partners and external researchers to develop innovative technologies that solve some of the complex and hardest sustainability problems as part of the listed examples above.
Key job responsibilities
- Develop scalable and effective machine-learning models and optimization strategies to solve business problems.
- Conduct research on new machine-learning and AI models and develop comprehensive data foundation, accurate and scalable methods to solve our hardest sustainability problems.
- Work closely with software engineers to deliver end-to-end solutions into production
- Partner with sustainability SMEs (carbon, water, waste, ESG, social responsibility, etc.), tech and science teams to drive modeling and technical design for complex problems, define • Develop scalable and effective machine-learning models and optimization strategies to solve business problems.
- Conduct research on new machine-learning and AI models and develop comprehensive data foundation, accurate and scalable methods to solve our hardest sustainability problems.
- Work closely with software engineers to deliver end-to-end solutions into production
- Partner with sustainability SMEs (carbon, water, waste, ESG, social responsibility, etc.), tech and science teams to drive modeling and technical design for complex problems, define
BASIC QUALIFICATIONS
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Develop scalable and effective machine-learning models and optimization strategies to solve business problems.
- Conduct research on new machine-learning and AI models and develop comprehensive data foundation, accurate and scalable methods to solve our hardest sustainability problems.
- Work closely with software engineers to deliver end-to-end solutions into production
- Partner with sustainability SMEs (carbon, water, waste, ESG, social responsibility, etc.), tech and science teams to drive modeling and technical design for complex problems, define
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in professional software development
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.