ML Data Infrastructure Engineer
Core
Design and build high-performance, globally distributed data processing infrastructure for model training and feature serving.
Role type
ML Data Infrastructure Engineer
Builds
High-availability ecosystem platform for ML model training and feature delivery
Domain
Advertising technology / Machine Learning Infrastructure
Deliverable
production ML models
Required skills
distributed systems engineering, high-throughput system design, performance optimization, data structures, fault tolerance
Preferred skills
MLOps, feature stores, model-serving systems, ML training pipelines
Technologies
Apache Spark, Flink
Responsibilities
Design and build data processing infrastructure for model training and feature serving; Collaborate with research teams on novel data processing architectures; Identify and resolve performance bottlenecks in the training data pipeline; Establish best practices and tooling for data infrastructure
Seniority
Mid-level, hands-on IC
