ML Data Infrastructure Engineer

Sourced from victra.careers

AppLovin's ML Data Platform team is hiring an ML Data Infrastructure Engineer to build high-performance, fault-tolerant data processing infrastructure for model training and feature serving. You'll design distributed data architectures, optimize training pipelines, and collaborate with research teams on emerging model paradigms. The role focuses on performance, reproducibility, and traceability across the ML data ecosystem.

• Design and build data processing infrastructure for model training and feature serving
• Collaborate with research teams to design novel data processing architectures
• Identify and resolve performance bottlenecks across the training data pipeline
• Establish best practices and tooling for data infrastructure used across ML teams

• 1-3 years of experience and a BS/MS in Computer Science
• Strong software engineering fundamentals with high-throughput, fault-tolerant distributed systems
• Hands-on experience with Apache Spark or Flink
• Solid grounding in data structures, systems design, and performance optimization
• Strong problem-solving skills and attention to detail

• Background in MLOps, Data Infrastructure, or ML Infrastructure
• Experience with ML training pipelines, feature stores, or model-serving systems