As a Senior Software Engineer, you will be an early member of the Eventual team with primary responsibilities around building out key features for the Daft distributed data engine.
You will be working on core architectural improvements to various components of Daft including:
Query Optimizer: intelligently optimize users’ workloads with modern database techniques
Execution Engine: improve memory stability through the use of streaming computation and more efficient data structures
Distributed Scheduler: improve Daft’s resource utilization, task scheduling and fault tolerance
Our goal is to build the world’s best open-source distributed query engine, and your work will play a key role in realizing that vision.
We are a young startup - so be prepared to wear many hats such as tinkering with infrastructure, talking to customers and participating heavily in the core design process of our product!
We are looking for a candidate with a strong foundation in systems programming and ideally experience with building distributed data systems or databases (e.g. Hadoop, Spark, Dask, Ray, BigQuery, PostgreSQL etc)
Our ideal candidate has:
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)
Most importantly, we are looking for someone who works well in small, focused teams with fast iterations and lots of autonomy. If you are passionate, intellectually curious and excited to build the next generation of distributed data technologies, we want you on the team!
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.
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.
A technical phone screen question over video call to understand your technical abilities.
Technical interviews with the rest of the Eventual team with questions to further understand your technical strengths, weaknesses and experiences.
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!
Eventual is a data platform that helps data scientists and engineers build data applications across ETL, analytics and ML/AI.
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.
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 AnyScale, 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!
