Software Engineer 4/5, Data and Feature Infrastructure, AI Platform

What you'll do

• Design and build a near-real-time feature computation engine for high-throughput training and low-latency inference.
• Operate and manage feature computation pipelines and serving infrastructure across multiple ML domains.
• Build and scale systems to accelerate training through performant data loading, transformation, and writing.
• Create frameworks to streamline the availability of new data for training and serving.
• Develop feature stores that enable feature discovery and sharing across various ML domains.
• Build a centralized embedding store to enable sharing across different business areas.
• Improve ML practitioner productivity by simplifying the definition and access of features and labels.

What we're looking for

• Experience in building ML or data infrastructure.
• Experience in building and operating 24/7 high-traffic and low-latency online applications.
• Experience with large-scale data processing frameworks such as Spark, Flink, and Kafka.
• Experience with data storage and serving technologies such as Iceberg and Cassandra.
• Experience in working with and optimizing Java and/or Python codebases.
• Experience with public clouds, especially AWS.
• Experience in building and operating ML feature stores, such as Chronon (preferred).
• Experience in building embedding-based retrieval systems (preferred).