Software Engineer, Data Systems
About the role
Software Engineer role on the Data Systems team at Eventual, building a high-throughput, petabyte-scale data engine for multimodal (video, lidar, telemetry) data to power frontier robotics and Physical AI models. Office in San Francisco, 4 days/week. Full-time, visa sponsorship available.
Responsibilities
- Multimodal Storage (Data Lake): built against modern columnar data lake formats (Apache Parquet, Apache Iceberg etc) optimized for high-dimensional video, lidar and sensor logs.
- Query Engine: build powerful querying capabilities with partitioning, indexing, query planning, embeddings/vector search for search and retrieval, and use of LLMs/VLMs for perception-based query predicates.
- Dataloading: Improve memory stability, throughput, and zero-copy data flow through streaming computation and line-rate CUDA tensor delivery to GPUs.
Qualifications
- Proven track record building resilient, high-throughput distributed systems or database engines using Rust or C++.
- 3+ years of experience diving deep into engine internals—such as vectorized execution, query planning/optimization, distributed task scheduling, or zero-copy networking.
- Practical exposure to scaling cloud infrastructure (AWS S3) and managing heavy-compute data pipelines.
- Bonus points for experience with CUDA, GPU streaming, or video decoding frameworks.
- High agency and adaptability to thrive in an autonomous, fast-paced startup environment building cutting-edge infrastructure for frontier robotics.
Skills
Benefits
- In-person tight knit team with 4x a week in office
- Competitive comp and startup equity
- Catered lunches and dinners for SF employees
- Commuter benefit
- Team building events & poker nights
- Health, vision, and dental coverage
- Flexible PTO
- Latest Apple equipment
- 401k plan with match
About Eventual
Building the AI data engine for any modality and scale
Every breakthrough AI application, from foundation models to autonomous vehicles, relies on processing massive volumes of images, video, and complex data. But today’s data platforms (like Databricks and Snowflake) are built on top of tools made for spreadsheet-like analytics, not the petabytes of multimodal data that power AI. As a result, teams waste months on brittle infrastructure instead of conducting research and building their core product. Eventual was founded in 2022 to solve this. Our mission is to make querying any kind of data, images, video, audio, text, as intuitive as working with tables, and powerful enough to scale to production workloads. Our open-source engine, Daft, is purpose-built for real-world AI systems: coordinating with external APIs, managing GPU clusters, and handling failures that traditional engines can’t. Daft already powers critical workloads at companies like Amazon, Mobileye, Together AI, and CloudKitchens. We’ve assembled a world-class team from Databricks, AWS, Nvidia, Pinecone, GitHub Copilot, Tesla, and more, quadrupling our size within a year. With backing from Y Combinator, Caffeinated Capital, Array.vc, and top angels from the co-founders of Databricks and Perplexity, we’re looking to double the team now. Join us—Eventual is just getting started. Please note we are looking for someone who is willing and able to come into our San Francisco office in the Mission district 4 days / week.
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