Technology is revolutionizing how we shop for everyday essentials! Are you interested in disrupting and redefining the way customers purchase online? Are you interested in using the latest advances in machine learning, big-data technologies, and LLMs to build online customer experiences for everyday essential products that can equal or even surpass an in-store experience? Amazon Consumables Science Team is reinventing the shopping experience for all customers across the largest selection of essential products to become the most trusted destination for everyday needs. The category is unique in retail with its vast customer base and products that are fundamental to daily life, from beauty and personal care to groceries and pet supplies. This is your chance to get in on the ground floor to build something entirely new and transform how people shop for their essential needs! To achieve our vision, we think big and tackle technological challenges every day. We need builders and disruptors who are not afraid to innovate! Our architecture and development processes support rapid experimentation, global deployments, and self-service capabilities that allow us to scale better.

We build:

* Amazon scale systems: All our technology needs to work at Amazon scale, serving millions of customers with millisecond-level latency.
* Personalization using machine learning: We use latest advances in ML and GenAI to provide better-personalized shopping experiences.
* Data & analytics pipelines: Robust data backbone and seamless ML pipelines is necessary for our systems to function smoothly at scale. We use the latest and greatest advances in AWS Technologies, data lakes, ML Engineering (RAGs, vector searches, lang chain, SageMaker Studio), and automation frameworks to build services and pipelines that can be deployed to production rapidly.



Key job responsibilities
* Work closely with senior engineers, product managers and business stakeholders to design and implement highly available back-end services;
* Convert a problem statement and requirements into a scalable and extendible design along with tasks;
* Write quality code as part of implementing aforementioned designs and deliver them in time;
* Develop personalized recommendation systems that help customers find the right beauty products based on their needs and preferences;
* Understand complex application data flows and bridge the gap between technical and business app requirement;
* Share expert knowledge in performance, large scale distributed system scalability, system architecture, and engineering best practices;

About the team
We are a passionate group of engineers, scientists, product managers, and designers who drive technological innovation to improve the customer shopping experience. We have a startup-like work culture where innovation is encouraged; we are never afraid to propose big ideas for fear of failing!