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EventualData Warehouse for ML/AI

Eventual is a data warehouse for ML/AI. We are building an integrated development experience for data scientists and engineers to build ML/AI applications which query and process multimodal data (images, video, audio and 3D scans). Daft (https://www.getdaft.io) is our open-sourced distributed data query engine. It has a Python Dataframe API and is built in Rust, providing both ease of use and performance for use-cases such as ML data engineering, training data ingestion and general data analytics. We are funded by investors such as 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.

2022-03-24
Active
Early
W22
5
B2B
United States of AmericaAmerica / CanadaRemotePartly Remote
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More About Eventual

Eventual: The Data Warehouse for ML/AI

The all-in-one platform for modern data workloads across data engineering, machine learning, and analytics.

Key Features

  • Python-native platform
  • Seamless integration with existing tools
  • Scalable data processing
  • Interoperability with diverse data types

Use Cases

  • Data engineering
  • Machine learning
  • Analytics
  • ETL processes

Pricing

Contact us for detailed pricing information tailored to your needs.

Teams

Eventual is built by experts in distributed data systems, machine learning, and high-performance computing:

  • Sammy Sidhu: High performance computing, prev. CTO @ DeepScale
  • Jay Chia: Cloud data systems for ML @ Freenome/Lyft
  • Clark Zinzow: Distributed data systems, built Ray Data @ AnyScale
  • Kevin Wang: Quant research @ Arrowstreet/Akuna
  • Colin Ho: Data systems @ Stripe/Coinbase

Join us today. We’re a fun-loving team passionate about building awesome systems. Come join us in our office in San Francisco! See Open Roles.