Climate Pledge Friendly helps customers discover and shop for products that are more sustainable. We partner with trusted sustainability certifications to highlight products that meet strict standards and help preserve the natural world. By shifting customer demand towards more sustainable products, we incentivize selling partners to build better selection, creating a cycle that yields significant environmental benefit at scale.
We are seeking a Senior Applied Scientist who is not just adept in the theoretical aspects of Machine Learning (ML), Artificial Intelligence (AI), and Large Language Models (LLMs) but also possesses a pragmatic, hands-on approach to navigating the complexities of innovation. You will take the lead in conceptualizing, building, and launching models that significantly improve our shopping experience. A successful applicant will display a comprehensive skill set across machine learning model development, implementation, and optimization. This includes a strong foundation in data management, software engineering best practices, and a keen awareness of the latest developments in distributed systems technology.
You will work with business leaders, scientists, and engineers to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable distributed ML models and services. The types of initiatives you can expect to work on include a) detection of sustainability intent in a customer's shopping journey, b) personalized recommendations that help our customers find the right sustainable products, c) strategies to incorporate sustainability features into ranking models, and d) models to measure the environmental and econometric impacts of sustainable shopping.
Key job responsibilities
To be successful, you must have expertise using machine learning, data mining, and statistical techniques to create actionable, meaningful, and scalable solutions to complex business problems. You should have a practical understanding of strength and weakness of various scientific approaches, and excellent communication skills to communicate complex technical concepts with a range of technical and non-technical audience.
As a Senior Applied Scientist for Climate Pledge Friendly, you will
- Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems.
- Collaborate with cross-functional teams to identify requirements for ML experiments, focusing on enhancing our mission understanding through innovative AI techniques.
- Design and implement scalable ML models capable of processing and analyzing large datasets to improve sustainable shopping.
- Leverage Agentic workflows, and tune foundational models (LLM/LMM/RAG), applying advanced ML techniques to optimize science solutions.
- Facilitate collaboration across teams working on similar problems, and serve as a technical lead and liaison for shared projects.
- Build a roadmap of science investments necessary for the team to evolve the shopping experience.
About the team
The Climate Pledge Friendly core team is highly motivated team of engineers, scientists, product managers, designers. This is still Day 1 for our program, and you will have the opportunity to help us craft a science based vision for the future. - 3+ years of building machine learning models for business application experience
- PhD, or Master's 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.
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Experience with conducting research in a corporate setting
- Experience with fine tuning Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) is advantageous
- Hands-on experience in building solutions for Recommendation Systems , Personalization, Indexing, User Behavioral Modeling, Ranking Algorithms, and relevant technologies
- Top tier AI publications is a strong plus
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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.
