ML Data Infrastructure Engineer

Applovin•Palo Alto, CA

About The Position

AppLovin makes technologies that help businesses of every size connect to their ideal customers. The company provides end-to-end advertising solutions for businesses to reach, monetize and grow their global audiences. As a member of our ML Data Platform team, you'll solve technical challenges, including upgrading and implementing state-of-the-art software infrastructure. The team builds a high-performance, high availability, globally distributed ecosystem platform of services that in turn provide the foundation for rapid development of novel new systems that integrate into that ecosystem and improve it.

Requirements

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

Nice To Haves

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

Responsibilities

Design and build data processing infrastructure for model training and feature serving, optimizing for performance, reproducibility, and traceability
Collaborate closely with research teams to design and implement novel data processing architectures for emerging model and training paradigms
Identify and resolve performance bottlenecks across the training data pipeline, from raw data ingestion to feature delivery
Establish best practices, tooling for data infrastructure used across ML teams