[Search & Discovery] Sr. Staff, Machine Learning Engineer (Ranking/Recommendations)

 

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

• Strongly own the Recommendation service, one of the most critical for Coupang to make sure we are wowing customers constantly.
• Collaborate tightly with multiple global teams across the company to co-build a world class recommendation system
• Mine vast amount of data to gain insights from customer behavior
• Develop new Machine Learning models and features to create new recommendation algorithm or improve existing algorithms
• Create data jobs to generate Machine Learning features; build and train new models; run experiments to validate and launch new models
• Mentor and grow engineers across the teams.

 

Qualifications

• 8+ years’ experience working with large-scale, complex datasets to extract robust features and create reliable machine learning models.
• Track record of diving into data to discover hidden patterns and solving problems with data science
• Fast paced self-learner with proven record of launching successful features and improving business metrics
• Tech lead working with coworkers across teams to solve critical customer problems
• Strong communication skills and full proficiency in English

 

Preferred Qualifications

• Professional Korean proficiency
• Master’s or Ph.D. degree in Computer Sci