Staff ML Engineer — Content Recommendation & Personalization

Coupang; Singapore; Vor Ort; SGD 140.000 - 210.000; Vollzeit

Zusammenfassung

Coupang Play is seeking an experienced Staff Machine Learning Engineer in Singapore to advance its large-scale content recommendation and personalization efforts. You will mine playback data, create features, train models, and build the framework for recommendations, collaborating closely with product and engineering teams.

You will own end-to-end model development, from data requirements to production rollout, including A/B testing and performance analysis, in a fast-paced environment at

Qualifikationen

• Bachelor’s degree in computer science, Electrical Engineering, Statistics, Mathematics, or a related field.
• 7+ years of experience building ML products with at least 2 years in content recommendation or ad personalization.
• Experience deploying large-scale recommendation systems in production.
• Proficiency in Python and at least one deep learning framework (PyTorch, TensorFlow, or Keras).
• Strong statistical background in experimentation and modeling.
• Strong product sense, self-starter and ability to drive critical projects in a fast-paced environment.
• Excellent communication skills in English and a collaborative mindset.

Aufgaben

• Build next-gen content recommendation and ad personalization systems.
• Define data requirements and coordinate with engineering and business teams for data collection and validation.
• Develop features for models and train relevant models using data and tools.
• Integrate model inference into production systems.
• Set up testing (A/B) and analyze results to gauge model performance.

Kenntnisse

Python

Deep learning

Big data

Model deployment

Experimentation

Communication

Ausbildung

Bachelor's degree in CS/EE/Stats/Math or related field

MS or PhD in CS/EE/Stats/Math (preferred)

Tools

PyTorch

TensorFlow

Keras

AWS

Jobbeschreibung

Coupang Play is seeking an experienced Staff Machine Learning Engineer in Singapore to advance its large-scale content recommendation and personalization efforts. You will mine playback data, create features, train models, and build the framework for recommendations, collaborating closely with product and engineering teams.

You will own end-to-end model development, from data requirements to production rollout, including A/B testing and performance analysis, in a fast-paced environment at