About Eventual

Eventual is a data platform that helps data scientists and engineers build data applications across ETL, analytics and ML/AI.

OUR PRODUCT IS OPEN-SOURCE AND USED AT ENTERPRISE SCALE

Our distributed data engine Daft is open-sourced and runs on 800k CPU cores daily. This is more compute than Frontier, the world's largest supercomputer!

Today's data tooling (Spark, Presto, Snowflake) was built for a world of tabular data analytics, but does not generalize to the needs of modern ML/AI such as multimodal data, heterogenous compute and user-defined Python algorithms.

Eventual and Daft bridge that gap, making ML/AI workloads easy to run alongside traditional tabular workloads.

Overview:

At Eventual, we are redefining the future of distributed data systems. As a Software Engineer - Storage, you will play a pivotal role in designing and implementing cutting-edge storage/data catalog solutions that power our high-performance computing and machine learning infrastructure. You will work closely with a world-class team of engineers to build scalable, resilient, and efficient data storage systems that support real-time and large-scale data workloads.

Key Responsibilities

• Design and build storage for AI/ML workloads: Design, develop, and optimize storage solutions for distributed data systems serving AI/ML workloads

• Optimize for performance: Analyze and improve the performance of storage components, reducing latency and optimizing throughput

• Data engine integrations: design and implement the storage layer for the Daft data engine to integrate effectively with both open data formats (e.g. Apache Parquet, S3, Apache Iceberg) as well as our proprietary storage solution

What we look for:

• Strong proficiency in systems programming with languages such as C++ or Rust.

• Experience with distributed storage systems (e.g., Ceph, HDFS, S3, RocksDB, or similar).

• Deep understanding of file systems, databases, and key-value stores.

• Familiarity with storage performance tuning, caching, and data replication strategies.

• Familiarity with cloud storage/data catalog technologies such as Apache Parquet, Apache Iceberg, Deltalake and AWS Glue.

• Hands-on experience with cloud storage solutions (AWS S3, GCP Cloud Storage, or Azure Blob Storage) is a plus.

• Background in high-performance computing or large-scale data processing is highly desirable.

• Excellent problem-solving skills and the ability to work in a fast-paced startup environment.

Benefits and Remote Work

We are believers in both having the flexibility of remote work but also the importance of in-person work, especially at the earliest stages of a startup. We have a flexible hybrid approach to in-person work with at least 3 days of in-person work typically from Monday - Wednesday at our office in San Francisco.

We believe in providing employees with best-in-class compensation and benefits including meal allowances, comprehensive health coverage including medical, dental, vision and more.

About the interview

INTRODUCTORY CALL [15M]

A short phone screen over video call with one of our co-founders for us to get acquainted, understand your aspirations and evaluate if there is a good fit in terms of the type of role you are looking for.

TECHNICAL PHONE SCREEN [1 HR]

A technical phone screen question over video call to understand your technical abilities.

TECHNICAL INTERVIEW PANEL [4 HR]

Technical interviews with the rest of the Eventual team with questions to further understand your technical strengths, weaknesses and experiences.

MEET THE TEAM

As many chats as necessary to get to know us - come have a coffee with our co-founders and existing team members to understand who we are and our goals, motivations and ambitions.

We look forward to meeting you!

WE'RE GROWING - COME GROW WITH US!

We are well funded by investors such as YCombinator, Caffeinated Capital, Array.vc and top angels in the valley from Databricks, Meta and Lyft.

Our team has deep expertise in high performance computing, big data technologies, cloud infrastructure and machine learning. Our team members have previously worked in top technology companies such as Amazon, Databricks, Tesla and Lyft.

We are looking for exceptional individuals with a passion for technology and a strong sense of intellectual curiosity.

If that sounds like you, please reach out even if you don't see a specific role listed that matches your skillsets - we'd love to chat!