About Coupang
We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did we ever live without Coupang?” Born out of an obsession to make shopping, eating, and living easier than ever, we are collectively disrupting the multi-billion-dollar commerce industry from the ground up and establishing an unparalleled reputation for being leading and reliable force in South Korean commerce.
We are proud to have the best of both worlds – a startup culture with the resources of a large global public company. This fuels us to continue our growth and launch new services at the speed we have been at since our inception. We are all entrepreneurial surrounded by opportunities to drive new initiatives and innovations. At our core, we are bold and ambitious people that like to get our hands dirty and make a hands-on impact. At Coupang, you will see yourself, your colleagues, your team, and the company grow every day.
Our mission to build the future of commerce is real. We push the boundaries of what’s possible to solve problems and break traditional tradeoffs. Join Coupang now to create an epic experience in this always-on, high-tech, and hyper-connected world.
Team Overview
The Recommendation team is responsible for the customers’ product discovery experience on Coupang, including recommendation quality, product ranking on category pages, and review ranking.
Recommendation is a fast-growing area, and we are working to improve the quality of recommendations to ensure that customers find the best products for them. We are aiming to provide customers with a ‘wow’ shopping experience by offering them with the products they like even before they express their intent, which is one of the best discovery experiences in e-commerce. We use the state-of-the-art Machine Learning and Deep Learning technologies to ensure the best quality of recommendations, and we are continuously innovating and building highly scalable systems to support the growing business and customer engagement.
Role Overview
As a Sr. Staff Ranking Engineer for Recommendations, you will be responsible for the design, development, maintenance, and improvement of the end-to-end recommendation quality and systems. This encompasses our online recommendation ranking models/systems, multiple data pipelines that produce the candidates and features (offline and online) used across various ranking algorithms, a serving system that produces the recommendation result and product ranking result across the Coupang. You will need to collaborate closely with the global teams that share ownership of customers’ product discovery experiences in Coupang. You will run experiments to validate in a controlled environment and launch any features and ranking improvements that would improve the customer experience.
Key Responsibilities
Qualifications
Preferred Qualifications
Recruitment Process
Details to Consider
Privacy Notice
https://www.coupang.jobs/en/privacy-policy/
Document Return Policy
Equal Opportunities for All
Coupang is an equal opportunity employer. Our unprecedented success could not be possible without the valuable inputs of our globally diverse team.
XPeng Motors is one of China’s leading smart electric vehicle (“EV”) companies. We design, develop, manufacture and market smart EVs...
How to applyAbout FullStack The Position What We Are Looking For Bachelor’s or Master’s degree in Computer Science, Engineering, Artificial Intelligence, Machine...
How to applyAWS Utility Computing (UC) provides product innovations – from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon...
How to applyMinimum qualifications: Bachelor’s degree or equivalent practical experience. 8 years of experience in software development, and with data structures/algorithms. 5...
How to applyProject Role : AI / ML EngineerProject Role Description : Develops applications and systems that utilize AI tools, Cloud AI...
How to applyAs a Senior Scientist at AWS AI/ML leading the Personalization and Privacy AI teams, you will have deep subject matter...
How to apply