4 days ago
Seoul, Korea, SouthStaff+
Responsibilities
- Design, build, and operate an end-to-end ML platform supporting data processing, feature engineering, model training, evaluation, deployment, monitoring, and experimentation.
- Design and develop high-throughput, low-latency real-time inference systems and ML APIs for user experiences.
- Ensure the stability, availability, observability, and operational efficiency of ML systems in large-scale production environments.
- Collaborate with ML scientists, data engineers, backend engineers, product managers, and content-domain experts to develop scalable ML solutions.
- Provide technical leadership across ML platform architecture, production ML operations, multimodal model usage, and engineering strategy.
- Advance recommendation quality and personalization to improve user engagement metrics such as viewing time and click-through rate.
Requirements
- Bachelor’s degree or higher in computer science, machine learning, artificial intelligence, or a related field.
- At least 7 years of experience developing and operating ML products, including at least 2 years with recommendation, personalization, or large-scale user-facing ML systems.
- Experience building real-time inference systems, ML APIs, and model-serving infrastructure in large-scale traffic environments.
- Experience using Python, PyTorch, Spark, Airflow, and modern ML frameworks and platform tools.
- Understanding of distributed systems, cloud infrastructure, microservices, containers, orchestration, and CI/CD.
- Experience operating production ML systems, including monitoring, observability, alerting, model performance management, data-quality validation, incident response, and reliability improvements.
- Strong communication and collaboration skills across multiple disciplines.
- Preferred experience includes recommendation systems and ranking models, multimodal or video-understanding models, or LLM-based model development and operations.
- Preferred qualifications include experience with model architecture, training, fine-tuning, evaluation, production deployment, large-scale distributed ML systems, or GPU-based training.
Benefits
- Permanent employment with a 12-week probationary period, which may be waived, shortened, or extended when business needs require.
- All interviews are conducted remotely.
- The recruitment process may close early once the position is filled.
Tech Stack
Categories
About Coupang
Coupang builds and operates a South Korea–focused e-commerce marketplace with an end-to-end logistics network (Rocket Delivery), plus food delivery, video streaming, and fintech under brands such as Coupang, Eats, and Play. Revenue comes from first-party retail, third-party marketplace services, advertising, and memberships (Rocket WOW). Founded in 2010, the company is headquartered in Seattle and is publicly listed on the NYSE (CPNG).