Job Information
Amazon Sr Applied Scientist, Climate Pledge Friendly in Seattle, Washington
Description
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 virtuous 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) personalized recommendations that help our customers find the right sustainable products on each shopping journey, b) automated solutions that combine ML/LLM and data mining to identify products that align with our sustainability goals and resonate with our customers' values, and c) 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
Collaborate with cross-functional teams to identify requirements for ML model development, focusing on enhancing our mission understanding through innovative AI techniques.
Serve as a technical lead and liaison for ML projects, facilitating collaboration across teams and addressing technical challenges.
Design and implement scalable ML models capable of processing and analyzing large datasets to improve sustainable shopping.
Lead the management and experiments of ML models at scale, applying advanced ML techniques to optimize science solutions.
Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems.
Build a roadmap of science investments necessary for the team to evolve product identification and the shopping experience.
About the team
The Climate Pledge Friendly core team is highly motivated team of engineers, product managers and 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.
We are open to hiring candidates to work out of one of the following locations:
Boston, MA, USA | New York, NY, USA | Seattle, WA, USA
Basic Qualifications
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
Preferred Qualifications
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 and Retrieval-Augmented Generation is advantageous
Hands-on experience in building solutions for Recommendation Systems , Personalization, Indexing, ANN, User Behavioral Modeling, Ranking Algorithms, NLP, Computer Vision and relevant technologies
Top tier AI publications is a strong plus
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
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.