ML Data Infrastructure Engineer
AppLovin · Palo Alto, CA
About this role
## ML Data Infrastructure Engineer **About the Role** As a member of the 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 provide the foundation for rapid development of novel new systems. **The Impact You'll Make** • 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 and tooling for data infrastructure used across ML teams **Required Qualifications** • 1-3 years of experience with a minimum 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 **Preferred Qualifications** • Background in MLOps, Data Infrastructure, or ML Infrastructure • Experience with ML training pipelines, feature stores, or model-serving systems **Compensation & Benefits** 💰 CA Base Pay Range: $150,000 – $224,000 USD 📊 Equity eligible 🏥 Medical, Dental, Vision, Life, Disability Insurance 🏦 401(k) Retirement Plan ⏰ Unlimited Discretionary Time Off + 10 paid holidays + 80 hours sick leave/year
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