Software Development Engineer II, Consumables Science Team

Amazon • Vancouver, British Columbia, Canada • 21h ago

Description

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.
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

Basic Qualifications

3 years of non-internship professional software development experience
2 years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
A willingness to dive deep, experiment rapidly and get things done

Preferred Qualifications

3 years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
Experience with AWS technologies (S3, EC2, Lambda, DynamoDB, RDS, CloudWatch, ElasticSearch etc.);
Experience designing and/or implementing automated software testing, deployment and performance analysis systems;
Experience writing testable code and automating test regressions;
Experience communicating technical problems to both technical and business audiences verbally and in writing;
Experience using Machine Learning and Generative AI to solve complex customer problems and create innovative, personalized shopping experiences that enhance customer satisfaction and decision-making;

Company

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