ML Data Infrastructure Engineer
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. To deliver on this mission, our global team is composed of team members with life experiences, backgrounds, and perspectives that mirror our developers and customers around the world. At AppLovin, we are intentional about the team and culture we are building, seeking candidates who are outstanding in their own right and also demonstrate their support of others.
Requirements
- 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
Benefits
- Competitive total compensation package
- Pay for performance rewards approach
- Equity
- Medical, Dental, Vision, Life, Disability insurance
- 401(k) Retirement Plan
- Unlimited Discretionary Time Off
- 10 paid holidays per year
- 80 hours of paid sick leave per year
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
