Job Description

The Machine Learning Platform team at DoorDash is seeking a Machine Learning Infrastructure Engineer to design, build, and optimize data pipelines for RAG systems. This role involves working with diverse data sources, building scalable indexing pipelines, and ensuring high-performance data ingestion into vector databases to enhance the accuracy and efficiency of LLM-based applications. This is a hybrid role based in San Francisco.

Responsibilities

• Design and build high-performance data pipelines
• Enhance the reliability, scalability, and observability of data and inference infrastructure
• Work closely with ML and Product Engineers to evolve the ML platform

Requirements

• 2+ years of experience in building ML infrastructure or related disciplines
• Strong background in building and optimizing data pipelines
• Understanding of vector databases and their role in RAG systems
• Experience with large-scale data infrastructure and real-time processing
• Problem-solving skills
• Passion for machine learning and data engineering

Benefits

• No benefits