Software Engineer, Systems

Eventual•San Francisco, CA

1d•$150,000 - $250,000•Onsite

About The Position

Eventual is building the future of data platforms for Physical AI, addressing the limitations of current systems that struggle with the massive multimodal datasets required for training AI models. Their open-source engine, Daft, is designed for this purpose and is already in use at major companies. The company has raised $30M and is backed by prominent investors and a world-class team. They are looking for a Software Engineer to join their small, collaborative team working 4 days a week in their SF office.

Requirements

Strong foundation in systems programming.
Experience with building distributed data systems or databases (e.g. Hadoop, Spark, Dask, Ray, BigQuery, PostgreSQL etc).
3+ years of experience working with distributed data systems (query planning, optimizations, workload pipelining, scheduling, networking, fault tolerance etc).
Strong fundamentals in systems programming (e.g. C++, Rust, C) and Linux.
Familiarity and experience with cloud technologies (e.g. AWS S3 etc).
Works well in small, focused teams with fast iterations and lots of autonomy.
Passionate, intellectually curious and excited to build the next generation of distributed data technologies.

Responsibilities

Build key capabilities for the Daft distributed data engine.
Work on core architectural design and implementation of various components in Daft.
Intelligently optimize users’ workloads with modern database techniques (Planning/Query Optimizer).
Improve memory stability through the use of streaming computation and more efficient data structures (Execution Engine).
Improve Daft’s resource utilization, task scheduling and fault tolerance (Distributed Scheduler).
Improve Daft integrations with modern data lake technologies such as Apache Parquet, Apache Iceberg and Delta Lake (Storage).
Tinker with infrastructure, talk to customers and participate heavily in the core design process of the product.