Senior Staff / Staff Machine Learning Engineer

Coupang · Singapore · по договорённости

Компания
Coupang
Город
Singapore
Зарплата
по договорённости
Уровень
senior
Формат
full_time
Иностранная компания
нанимает русскоязычных

Company Introduction

We exist to wow our customers. We know we’re doing the right thing when we hear our customers say, “How did I 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 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

At Coupang, we invest in providing the best product experience for our customers. The AI and Knowledge Engineering team’s mission is to provide the best possible technical solution to achieve the optimal experience for our customers. We innovate and advance the space of Knowledge Graphs, AI agents, LLMs, AIGC, ML, NLP, CV and multi-modal models.

We are looking for engineers who want to work on cutting edge technology, that is the intersection of Semantic knowledge bases, AI agents, NLP, LLM, AIGC, ML and software engineering. Come join us to help create a world class team advancing the AI/NLP/AIGC/ML/LLM/RL/Knowledge Graph technologies.

What You Will Do

Work on GenAI, AI agents' systems to solve complex eCommerce scenarios.

Develop large language and vision understanding/generation models for predictive and compound AI Models

Train foundational models that can help with building learning systems.

Define process and experiments for an E2E foundation model.

Build E2E AI pipelines for storing/servicing foundational models.

Mentor and guide team members on frameworks, methodologies related to data lakes, data normalization, dimension reduction, visualization, statistical models.

Ensure Model training is security, compliance aware.

Collaborate with cross-team members to understand the requirements ensuring the foundational models; knowledge captured aligns with the company’s overall AI strategy.

Basic Qualifications

5+ years of d emonstrated data science, experience in building large scale foundational models for eCommerce scenarios.

Expertise in large language model post-training and deployment.

Deep understanding of AI/LLM /AIGC /ML architecture.

Strong statistical/mathematical background in defining metrics, learning functions, and result analysis.

Significant experience in SQL, Python, P ySpark , Scala and R

Proficiency in P yTorch / TensorFlow, Spark, BigQuery

Proficiency in AI coding Cursor/Windsurf/Claude Code/Codex.

Experience creating complex data visualization tools, frameworks, and techniques.

Experience in dimension reduction in big data.

Proficient in cloud analytical stacks [ Lakes, warehouse, ETL pipelines]

Experience with inference platforms in AWS, Azure, and other open-source platforms.

Result-oriented, with a bias towards customer obsession, flexibility, and impact.

Strong written and verbal communication and teamwork skills

Passion for Large language models, NLP, and Machine Learning at scale

Education: B.S, M.S in Computer science or Mathematics, or related field

Recruitment Process

Application Review - Job Fit Interview - Focus Interview – Offer

The exact nature of the recruitment process may vary according to the specific job and may be chan

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