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Alluxio

Data management platform for AI workloads

Staff Software Engineer - Distributed System Development

Backend EngineeringConfirmed live in the last 24 hours
Full-timeFoster City, CA, USAIn-person

About the Job

Requirements

  • At least 1–2 years in a technical leader role.
  • A bachelor's degree in Computer Science, a similar technical field of study, or equivalent practical experience.
  • Software development experience in one or more general-purpose programming languages, including Java, C++, C, or Go.
  • Experience working with at least two of the following: distributed and parallel systems, distributed storage systems, architecting large-scale software systems, or security software development.
  • Working proficiency and communication skills in verbal and written English.

Responsibilities

  • Lead and evolve the Alluxio project, solving problems in distributed data services, memory and data-structure efficiency, thread concurrency, locking optimizations, and caching policies and implementation.
  • Develop solutions that scale systems to thousands of nodes while providing data durability and high availability.
  • Lead team members in taking creative solutions from concept to completion.
  • Contribute to product architecture and implement technical direction in collaboration with product management.

Desired Qualifications

  • A master's or PhD degree, further education, or equivalent practical experience in engineering, computer science, or another technical-related field.
  • Proficiency in one or more general-purpose programming languages, including Java, C++, C, or Go.
  • Interest and ability to learn other coding languages as needed.
  • Experience contributing to or maintaining an open-source project.
  • Contributed or currently contributing to Alluxio.

About the Company

Alluxio

Data management platform for AI workloads

Alluxio provides a data management platform for AI and ML workloads. It sits between compute and storage with two products, Alluxio Enterprise Data and Alluxio Enterprise AI, offering a unified interface to manage data across clouds, regions, and storage systems. This helps reduce data silos, minimize data movement, and improve data access latency, boosting GPU utilization and accelerating model training and serving. The goal is to simplify data engineering, cut infrastructure complexity and cost, and help enterprises accelerate their AI initiatives.

Company size
51-200
Company stage
Series C
Total funding
$81.5M
Headquarters
San Mateo, CA
Founded
2015

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