Hiring Open Source Software Engineering Intern | Eventual

Open Source Software Engineering Intern


Date listed

1 month ago

About Eventual:

At Eventual (YC W22), we are building Daft, the open-source framework for processing complex data.

Data processing systems today are highly optimized for simple tabular data. However, much of the useful data in the world is in a more complex form, such as media (e.g. images, video, audio), scientific formats (e.g. genomes), and ML artifacts (e.g. embeddings). There are many challenges today that make processing complex data much more difficult than working with simple tabular data. Our goal is to make working with complex data as easy as working with simple data, and become the de-facto solution for building applications on top of complex data.

You would be joining a small, fast-moving team of engineers with deep expertise across related domains: big data, distributed systems, machine learning, self-driving, genomics, and high performance computing.

About the role:

As a software engineering intern, your primary responsibilities would be contributing to the development of the open-source Daft distributed dataframe. Development moves quickly here, but here are some projects you might expect to work on:

  1. Implementing algorithms on complex data types, such as embedding similarity or image kernels
  2. Improving performance of distributed join operations
  3. Building integrations for high-performance data loading

We are a young startup, so do be prepared to wear many hats - tinkering with infrastructure, talking to users, and participating in design processes with the team!

About you:

You will want to be comfortable working on a novel distributed data processing system. Some things that will be important are:

  1. Industry or research experience working with distributed systems, especially data-intensive systems such as Spark, Dask, or Ray.
  2. Experience with Arrow-based frameworks.
  3. Familiarity with Python or Rust.
  4. A strong sense of ownership and autonomy; a desire to build good systems for users.

Big nice to haves are:

  1. Experience working on production machine learning systems.
  2. Experience with compilers or query optimization.

Office and benefits:

Our office setup is hybrid remote, with three in-person days a week. We are in our San Francisco office Wednesday to Friday.

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