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About the Role
As a Software Engineer on the Systems team, you will build key capabilities for the Daft distributed data engine, focusing on core architectural design and implementation. You will have the autonomy to scope and solve difficult technical challenges with guidance from an experienced team.
Responsibilities
- Optimize user workloads using intelligent planning and query optimization techniques.
- Enhance memory stability through streaming computation and efficient data structures in the execution engine.
- Improve Daft's resource utilization, task scheduling, and fault tolerance with the distributed scheduler.
- Enhance Daft's integrations with data lake technologies like Apache Parquet, Apache Iceberg, and Delta Lake.
- Contribute to infrastructure, customer interactions, and core product design processes.
Requirements
- Strong foundation in systems programming.
- Experience building distributed data systems or databases (e.g., Hadoop, Spark, Dask, Ray, BigQuery, PostgreSQL).
- 3+ years of experience with distributed data systems, including query planning, optimizations, workload pipelining, scheduling, networking, and fault tolerance.
- Strong fundamentals in systems programming (e.g., C++, Rust, C) and Linux.
- Familiarity and experience with cloud technologies (e.g., AWS S3).
- Ability to work effectively in small, focused teams with fast iterations and high autonomy.
- Passion, intellectual curiosity, and excitement for building next-generation distributed data technologies.
Skills
- Systems programming
- Distributed data systems
- Query planning
- Optimizations
- Workload pipelining
- Scheduling
- Networking
- Fault tolerance
- C++
- Rust
- C
- Linux
- Cloud technologies
- AWS S3
Location
- San Francisco Mission district office
Work Type
- In-person
- 4 days/week in office
Experience Level
- 3+ years of experience working with distributed data systems
Benefits
- Competitive compensation
- Startup equity
- Catered lunches and dinners
- Commuter benefit
- Team building events & poker nights
- Health, vision, and dental coverage
- Flexible PTO
- Latest Apple equipment
- 401k plan with match
About the Company
- Eventual was founded in 2022 to address the limitations of current data platforms for AI training data.
- Their open-source engine, Daft, is a distributed data engine purpose-built for multimodal AI.
- Daft is already processing petabytes of data daily at major companies like Amazon and FAANG.
- They are building a video-native index on top of their engine for Physical AI.
- The company has raised $30M from prominent investors including Felicis, CRV, and Microsoft M12.
- The team comprises experienced professionals from companies like AWS, Render, Pinecone, and Tesla.
- They are focused on powering the next generation of Physical AI.