Sr Staff Machine Learning Engineer

Coupang•Seattle, WA

About The Position

The Search & Discovery organization is responsible for optimizing customers' navigation experience and driving long-term growth. Every week millions of customers use search in our app or on coupang.com, more than one third of them make purchases. Over half of the Coupang sales are directly attributed to search and recommendation. Many business initiatives and growth strategies are driven or boosted by ranking and recommendation. This role is an opportunity to build scalable offline and online ML platforms to support ranking and recommendation, and business decision making. You will be handling billions of records of user interaction data, and petabytes of raw log files, and transforming them into data objects that can be easily consumed by engineers and scientists. You will also be responsible for serving complex ML models in real time to help millions of Coupang customers search and discover products. If you are passionate about big data engineering and scalable serving systems, you want to make real business impact, and you are a true problem solver, this is the right job for you.

Requirements

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

Nice To Haves

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, Scikit-learn, Keras, XGBoost, LightGMB, and H2o.ai
Experience with ML lifecycle tools such as MLflow, Kubeflow, Weights & Biases, or Amazon SageMaker
Excellent communication skills with the ability to explain complex technical concepts to both technical and non-technical stakeholders
Demonstrated ability to work independently and manage ambiguity in fast-paced environments

Responsibilities

Design features and build large-scale machine learning models and systems to improve ad targeting, relevance, ranking, and engagement
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
Build and optimize ML pipelines using tools such as Apache Spark, Airflow, Kubeflow, and MLflow, ensuring reproducibility, scalability, and operational excellence
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
Mentor and grow engineering talent, fostering a culture of technical excellence, experimentation and continuous learning