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 Series A and seed funding from Felicis, CRV, Microsoft M12, Citi, Essence, 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're looking for individuals who are excited to be a part of a tight-knit team working together 4 days / week in our SF Mission district office.
Your Role:
As a Software Engineer working on our Data Platform, you will be responsible for building Eventual's core products and architecture. You will ship features that will be immediately used by our customers and will work with a tight-knit team that values open communication and cross-functional collaboration. We move quickly to solve a wide range of complex technical and product challenges. While we are an experienced team that can provide constant guidance and mentorship, we value engineers who can autonomously scope and solve difficult technical challenges.
Design and scale resilient backend services and distributed data systems.
Work closely with cross-functional product and customer-facing teams to understand requirements and ship thoughtful solutions.
Orchestrate compute workloads and container infrastructure across cloud environments (Kubernetes, Slurm).
Build high-performance data applications, query tools, and data visualization platforms.
Optimize cloud storage architectures and system pipelines for throughput, reliability, and cost-efficiency.
We are looking for strong engineers who are problem-solvers at heart—combining excellent coding and architectural fundamentals in languages like Rust, C++, Python, or Go with a drive to reach for lower-level primitives when performance and efficiency demand it. We look for engineers with a technical spike in at least one of our specialized focus areas, though expertise across all of them is not required.
Areas that are highly relevant to the work that we do at Eventual, we only ask for expertise in one of these areas:
ML/AI platform
Search/recommendations platform
Computer vision
Computer graphics
Data services (data catalogs, data lakehouses, query engines)
Large-scale batch/streaming jobs
Deep expertise in storage infrastructure (cloud object storage, pubsub, queuing etc)
Experience with GPU management and orchestration
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!
Skills Required
- Proficiency in one or more languages: Rust, C++, Python, or Go
- Design and scale resilient backend services and distributed data systems
- Orchestrate compute workloads and container infrastructure across cloud environments (Kubernetes, Slurm)
- Experience with GPU management and orchestration, including GPU clusters
- Expertise in at least one specialized area: ML/AI platform, search/recommendations, computer vision, computer graphics, data services, large-scale batch/streaming jobs, or storage infrastructure
- Optimize cloud storage architectures and system pipelines for throughput, reliability, and cost-efficiency
- Strong coding and architectural fundamentals and ability to work autonomously on complex technical challenges
- Work onsite in the San Francisco Mission District office four days per week
What We Do
Eventual is building a Data Warehouse from the ground up that is designed to tackle the challenges of working with traditional data engineering and analytics alongside modern ML/AI workloads. Eventual has raised over $2.5M from investors including YCombinator, Array VC, Caffeinated Capital and top Silicon Valley executives and founders in companies such as Meta, Lyft and Databricks.
