Join us at the forefront of Amazon's sustainability initiatives to work on environmental and social advancements to support Amazon's long term sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people.
The Worldwide Sustainability (WWS) organization capitalizes on Amazon’s scale, speed, and ability to build, invent and simplify, a more resilient and sustainable company. We manage our social and environmental impacts globally, and drive solutions that enable our customers, businesses, and the world to become more sustainable.
We are seeking a Machine Learning Research Engineer to develop advanced AI solutions for sustainability. The role requires experience in using in Generative AI (GenAI), Large Language Models (LLMs), and Agentic AI. This role involves defining strategy and implementing tools to identify, ingest, harmonize, and maintain diverse datasets (e.g., emissions, geospatial, materials, supply chain graphs) from internal and external sources. These datasets are critical for unlocking AI capabilities across Amazon-wide sustainability initiatives, including environmental footprinting, materials innovation, and supply chain risk management.
The engineer will build data and modeling pipelines for ingestion, pre-processing, and post-processing, generating scientifically consistent and traceable data-cards and model performance metrics to inform business decisions. They will derive insights, build data models, and develop machine learning and LLM solutions for sustainability, collaborating with scientists on data engineering tasks (transformation, embeddings, feature engineering, and versioning).
The role also involves leveraging Agentic AI agents for autonomous information extraction, advanced data scraping, and other foundational engineering tasks to expand the data/model catalog and drive innovative sustainability solutions. If passionate about applying advanced AI paradigms to complex sustainability challenges at scale, consider joining our team.
Key job responsibilities
- Data Modeling & Infrastructure: Design, build, and optimize robust data and modeling pipelines for sustainability applications. This includes the development of sophisticated Retrieval-Augmented Generation (RAG) pipelines, leveraging techniques such as custom vector indexing and hybrid search strategies (combining methods like OpenSearch and dense embeddings) for enhanced data retrieval and model performance. Ensure traceable data cards and implement rigorous model performance metrics to inform strategic business decisions.
- Intelligent Data Acquisition & Curation: Implement scalable solutions for data scraping, cleaning, and preparation. Utilize Agentic AI and LLMs to automatically uncover relevant signals and extract information from diverse unstructured data sources, including textual data and scientific reports.
- Cross-Functional Collaboration & Strategic Impact. Partner closely with scientists, software developers, and sustainability specialists to define data needs, refine modeling requirements, and communicate actionable insights to stakeholders. Drive the adoption of advanced AI techniques to achieve ambitious sustainability targets across Amazon
- AI Innovation & Continuous Learning: Stay updated with emerging data science methods, ML/LLM technologies, and emerging datasets to continuously improve our sustainability domain-specific knowledge bases and analytical capabilities
- Continuously research and integrate data science methodologies, agentic AI and LLM advancements, and emerging datasets. This fosters continuous improvement in Amazon’s sustainability knowledge bases and analytical capabilities.
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, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Inclusive Team Culture:
It’s 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:
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll 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, there’s nothing we can’t achieve.
