Staff Machine Learning Engineer (CMG Engineering)

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’re collectively disrupting the multi-billion-dollar e-commerce industry from the ground up. We are one of the fastest-growing e-commerce companies that established an unparalleled reputation for being a dominant 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 entrepreneurs 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. 

Role Overview 

As our Staff Machine Learning Engineer for Coupang Ads Technology (Ads Tech), you will be responsible for understanding users’ shopping journeys, developing machine learning models, optimization algorithms and new product features for our advertising platform. 

Coupang Ads Technology (Ads Tech) team is responsible for providing vendors that sell their products on Coupang with a host of marketing products and services. Our group is responsible for advertising brands and products inside our e-commerce website. 

This is an opportunity to be part of building up a new development organization with strong revenue potential inside a successful company. We’re building full-stack engineering teams to handle large scale advertising problems, including real-time behavioral targeting, auctioning and bidding systems and search-based advertising. 

In this role you will be responsible for innovating and building our new ad quality stack for our ads platform and eventually extend it into a full ad exchange, DSP, and SSP. 

What You Will Do 

• Design and implement large-scale ML systems for search ranking, semantic retrieval, query understanding, and personalized product discovery using state-of-the-art techniques such as transformer-based models, contrastive learning and vector search 
• Drive innovation in search relevance and user intent modeling using large language models (LLMs), embedding-based retrieval, and multi-modal learning 
• Define and track key performance metrics to evaluate model impact and identify high leverage opportunities for improvement 
• Collaborate cross-functionally with product, engineering and data science teams to align technical solutions with business goals and customer experience 

Basic Qualifications 

• Bachelor's degree in computer science, electrical engineering, mathematics, statistics or closely related fields
• 4 years of professional experience in applied machine learning
• Experience in machine learning, deep learning, and statistical modeling
• Proficiency in Python and/or Java, with experience in building production grade ML Systems

Preferred Qualifications 

• Master’s or PhD in relevant technical fields
• Experience with search systems, information retrieval or recommendation engines
• Experience with LLMs, embeddings, and vector search technologies
• Experience with cloud platforms such as AWS, Google Cloud Platform including services like Vertex AI, BigQuery or SageMaker
• Experience working in startup or high-growth environments
• Proven ability to lead-cross-functional teams and deliver results in a multicultural, global organization
• Hands-on experience with modern ML frameworks such as TensorFlow, PyTorch, Scikitlearn, Keras, XGBoost, LightGMB, and H2o.ai
• Experience with ML lifecycle tools such as MLflow, Kubeflow, Weights & Biases, or Amazon SageMaker