Software Engineer 4 – 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.
• Create frameworks to streamline data availability for training and serving new features.
• Develop scalable systems that accelerate training through efficient data loading and transformation.
• Build centralized feature stores enabling discovery and sharing of datasets across various business areas.
• Collaborate with domain experts to ensure high-quality features and labels for ML models.

What we're looking for

• Extensive experience in building and managing ML infrastructure.
• Proficient in large-scale data processing frameworks like Spark, Flink, Kafka.
• Expertise in data storage technologies including Iceberg and Cassandra.
• Strong background in optimizing Java and Python codebases for performance.
• Hands-on experience with public cloud platforms, particularly AWS.
• Passionate about enhancing user experiences for ML practitioners.