Software Engineer, AI Infrastructure

About Eventual

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, 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.

Key Responsibilities:

• Design and build highly reliable and resilient products and features.

• Work closely with cross-functional product and customer-facing teams to understand requirements and ship thoughtful solutions.

• Write high-quality, extensible, and maintainable code.

• Design and build scalable applications and components.

• Architect and operate Kubernetes clusters optimised for GPU workloads.

• Build multi-tenant and dedicated environments for GPU workloads.

What we look for:

• 3+ years of experience working with complex infrastructure projects, ideally involving GPUs.

• Experience supporting ML/AI workloads.

• Experience optimising GPU utilisation and job placement through scheduler extensions, such as kube-scheduler plugins, Slurm and Volcano.

• A unique startup growth mindset of responsibly take on tech debt for velocity and building for future extensibility

• Familiarity and experience with cloud technologies (e.g. AWS S3 etc)

• Experienced with taking a product from ground zero to production.

• Most importantly, we are looking for someone who works well in small, focused teams with fast iterations and lots of autonomy. If you are passionate, intellectually curious and excited to build the next generation of distributed data technologies, we want you on the team!

Perks & 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!