High-performance distributed caching for AI workloads
Alluxio builds a distributed caching layer between compute frameworks and storage systems like S3, GCS, HDFS. It serves AI/ML and analytics teams by accelerating data access for training, inference, and queries. This reduces I/O latency and costs without data migration or code changes.
Defines and executes AI systems strategy for Alluxio's data platform, focusing on inference, training, and agentic workloads. Collaborates with engineering and AI teams to optimize latency, throughput, and integrations with frameworks like PyTorch and Ray. Requires 5-9 years in AI infrastructure or ML platforms.
Senior Software Engineer designs and optimizes distributed systems for Alluxio's data orchestration platform, focusing on caching, metadata management, I/O performance, and fault-tolerance in multi-cloud environments. Requires strong experience in Java/C++/Go and distributed storage technologies like Spark, Hadoop, and Kubernetes.
Staff Software Engineer designs and implements core components of Alluxio's distributed data orchestration platform, optimizing caching, metadata, and I/O for large-scale AI/ML workloads across multi-cloud environments. Requires strong distributed systems expertise in Java/C++/Go and technical leadership.