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Mid-level generalist title with strong startup brand and 5+ years requirement increases applicant density.
Role requires specialized distributed data systems and Ray experience, limiting cross-industry transferability.
Explicit 5+ years plus mandatory distributed systems, data processing, and system design requirements.
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Build, optimize, and scale Ray’s Datasets library to enhance usability, performance, and stability of distributed data processing.
Develop and improve core Ray components focused on data performance, integration with ML training and data sources, and streaming workloads.
Lead efforts on stability testing and differentiate data operations for Anyscale hosted Ray service.
At least 5 years of relevant work experience.
Strong knowledge of algorithms, data structures, and system design.
Experience building scalable and fault-tolerant distributed systems.
Experience with data processing frameworks or database internals such as Spark or Dask; experience with streaming is a plus.
Experienced in large-scale distributed data systems and familiar with Ray’s architecture or similar frameworks.
Capable of contributing to and optimizing open-source distributed computing projects with a strong focus on data processing.
Comfortable working on both core distributed systems and their integration with machine learning workflows and streaming data.