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.
• Implement data pipelines for model training, fine-tuning, and evaluation across diverse data sources.
• Optimize production models 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.
• 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, shell scripting, streaming and batch data pipelines, vector databases, DBT, BigQuery, BigTable, or equivalent.
• Proficiency with orchestration tools.
• Experience running machine learning in parallel environments such as distributed clusters and GPU optimization.
• Ability to communicate complex ML concepts to both technical and non-technical audiences.
• Availability to perform on-call work.