Staff Machine Learning Engineer

Coupang•Seattle, WA

2d•$164,000 - $282,000

About The Position

As our Staff Machine Learning Engineer for Coupang Media Group (CMG), Offsite Ads, you will be responsible for defining and building the next generation of machine learning systems, optimization platforms, and AI-native advertising products that power Coupang's rapidly growing offsite advertising business. The Coupang Media Group (CMG) provides advertisers with a comprehensive suite of marketing solutions designed to help brands reach customers and accelerate business growth. While CMG established a leading advertising marketplace within Coupang's ecosystem, Offsite Ads extends advertiser reach beyond Coupang-owned properties, enabling brands to engage customers across the broader internet while leveraging Coupang's unique commerce signals, first-party audience assets, and deep understanding of shopper intent. Since its inception in 2025, the Offsite Ads business has experienced exceptional growth, achieving more than 2x year-over-year revenue growth for consecutive years. As we continue to scale, we are investing heavily in world-class machine learning, large-scale AI infrastructure, and next-generation advertising technologies to build one of the industry's most advanced commerce media platforms. This is a unique opportunity to join and shape a fast-growing organization with significant revenue impact and strategic importance to Coupang. You will work on some of the most challenging problems in modern advertising, including large-scale prediction systems, bidding optimization, auction dynamics modeling, generative retrieval, foundation models, LLM-powered advertising solutions, and agentic AI systems. Our vision extends beyond traditional offsite advertising. We are building the foundational technology that will evolve into a comprehensive advertising ecosystem spanning demand-side platforms (DSP), supply-side platforms (SSP), ad exchanges, and AI-powered marketing solutions that connect advertisers with customers across the open internet.

Requirements

Bachelor's degree in Computer Science, Machine Learning, Statistics, Mathematics, Electrical Engineering, or a related quantitative field.
6+ years of industry experience developing and deploying machine learning solutions in production environments.
Strong foundation in machine learning, deep learning, statistical modeling, optimization, and large-scale data systems.
Hands-on experience developing production-grade ML systems using Python and/or Java.
Strong experience with PyTorch and modern deep learning architectures for prediction, ranking, recommendation, retrieval, or optimization problems.
Demonstrated ability to solve complex and ambiguous business problems through data-driven analysis and machine learning innovation.
Proven track record of owning large technical initiatives and delivering measurable business impact.

Nice To Haves

Master's degree or PhD in Computer Science, Machine Learning, Statistics, Mathematics, or a related field.
Experience in digital advertising, recommendation systems, ranking systems, marketplace optimization, or large-scale machine learning.
Experience with modern AI technologies, including LLMs, generative AI, embedding models, retrieval systems, or agentic AI.
Strong expertise in PyTorch and developing large-scale production machine learning systems.
Experience with distributed training, model serving, and ML platforms in cloud environments.
Familiarity with ML tools and frameworks such as PyTorch, XGBoost, LightGBM, Scikit-learn, MLflow, Kubeflow, Spark, and Airflow.
Demonstrated ability to solve ambiguous problems, drive technical strategy, and deliver measurable business impact.
Strong communication and collaboration skills, with the ability to influence stakeholders across multiple functions.
Comfortable operating in a fast-paced, high-growth environment with a strong sense of ownership and customer focus.

Responsibilities

Design and build machine learning models and systems that improve ad targeting, ranking, bidding, and campaign performance across Coupang's Offsite Ads platform.
Develop large-scale prediction and optimization models, including CTR, CVR, GMV, and bidding optimization.
Apply modern AI technologies such as LLMs, embeddings, agentic AI, and deep learning to solve complex advertising challenges.
Build scalable ML infrastructure and production systems that enable rapid experimentation and reliable model deployment.
Define success metrics, evaluate business impact, and continuously improve model performance through data-driven experimentation.
Partner closely with Product, Engineering, Data Science, and business teams to solve high-impact customer and advertiser problems.
Drive projects from concept to production with strong ownership and accountability for business outcomes.
Mentor engineers and contribute to a culture of technical excellence, innovation, and continuous learning.