Machine Learning Engineer

What you'll do

• Develop and deploy Generative AI, NLP, and HSTU-based recommendation models at scale.
• Design and implement scalable AI/ML system architectures to support production models.
• Build inference pipelines to process billions of events for real-time recommendations.
• Create data pipelines for training, fine-tuning, and evaluating models across diverse data sources.
• Optimize production performance using negative sampling, ANN search, and distributed GPU training.
• Experiment with novel machine learning architectures to improve merchant and consumer experiences.

What we're looking for

• Mastery in recommendation systems, Generative AI, or Large Language Models (LLMs).
• End-to-end experience training, evaluating, testing, and deploying machine learning products at scale.
• Experience building data pipelines and driving ETL design decisions using disparate data sources.
• Proficiency in Python and shell scripting.
• Proficiency with streaming/batch data pipelines, vector databases, DBT, BigQuery, or BigTable.
• Experience running machine learning in parallel environments including distributed clusters and GPU optimization.
• Ability to communicate complex ML concepts to both technical and non-technical audiences.