Staff Machine Learning Engineer

Coupang•Mountain View, CA

14h

About The Position

As our Staff Machine Learning Engineer for Coupang Media Group, Ads Quality, you will be responsible for developing, designing machine learning models, optimization algorithms and new product features for our advertising platform. The Coupang Media Group (CMG) is responsible for providing vendors that sell their products on Coupang a host of marketing products and services. We launched Product Ads performance advertising marketplace late in 2018. We have grown rapidly to over 10,000 active advertisers and 150M daily ad impressions in only 5 months’ time. Our group is responsible for advertising brands and products inside our e-commerce website. To get an idea of how valuable that is, both Alibaba and Amazon make more money on advertising than on selling products. 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. We are in the growth phase of the organization, so you’ll be a part of managing the transition from growth phase to enterprise processes. 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. We currently handle about 1bn impressions per day from internal traffic alone.

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