At Eventual, we are looking for the key individuals who are excited to build a new product and to grow with our company. Our team is small but packs a punch, and we come from backgrounds in genomics, self-driving and high performance computing. We love working on large ambitious projects but also enjoy a strong sense of camaraderie and never forget to work hard/play hard!
Key Responsibilities
As a Distributed Data Systems Engineer, you will be a founding member of the Eventual team with primary responsibilities around building out DaFt (our open source framework which will be the de facto solution for building applications on complex data such as images, audio and video), as well as the infrastructure that supports it on the Eventual Cloud Platform.
Some projects that you can expect to work on include:
- Query Optimization to optimize DaFt’s distributed execution plans
- Code generation to translate high level DaFt Dataframe query plans into instructions that can run on various backends including Spark, Ray, and the Eventual Cloud
- Building systems to optimize workload scheduling for maximal resource utilization
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!
What we look for
We are looking for a candidate with a strong foundation in systems programming and with experience with building distributed data systems (e.g. Hadoop, Spark, Dask, Ray).
Our ideal candidate has:
- 3+ years of experience with building the internals of distributed data systems (workload pipelining, scheduling, networking, fault tolerance etc)
- Experience with workload orchestrators such as Kubernetes/Mesos/Yarn
- Strong fundamentals in systems programming and Linux
- Works well in small focused teams with fast iterations and lots of autonomy
Nice to haves that will help in your day-to-day work:
- Experience with containerization technologies
- Experience with building compilers or query optimization
- Experience with GPUs and with CUDA
- Experience with building production machine learning systems
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 Wednesday - Friday 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.
Eventual
