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About the Role

As a Fullstack Engineer, you will own the product surface that researchers interact with. This interface allows them to explore their data corpus, write natural-language queries, review results, and ship curated datasets for training runs. You will be responsible for designing and building visualizations, query authoring tools, dataset versioning, and integration APIs. You will work directly with researchers, iterating quickly and shipping to production weekly.

Responsibilities

Design and build the product UI for exploring, querying, and curating multimodal datasets, including video playback, clip-level annotation, and visualizations.
Design and build the APIs that drive the UI and integrate with customer training stacks.
Build analytics to help researchers understand their corpus, such as distributions, dataset composition over time, and query result quality.
Collaborate closely with Visual Understanding, Dataloading, and Storage teams to ensure the product surface is a fast layer over the platform.
Gather requirements directly from researchers at partner labs and translate them into shipped features rapidly.
Write high-quality, extensible, and maintainable code, managing technical debt deliberately for velocity.

Requirements

Fullstack engineering experience across web applications, developer-facing products, or data products.
Proven track record of shipping core product features with strong user obsession.
Direct collaboration with users to gather requirements, manage feedback, and provide timely support.
Comfort with the full stack: modern frontend frameworks, backend services, APIs, and cloud infrastructure (AWS S3, etc.).
Experience taking a product from inception to production.
Judgment to balance taking on technical debt for velocity versus investing in extensibility.
Bias toward shipping features quickly.

Skills

Frontend frameworks
Backend services
APIs
Cloud infrastructure
Python
Rust

Location

San Francisco Mission district office

Work Type

4 days/week in office
Full-time

Experience Level

Fullstack engineering experience

Benefits

Competitive compensation
Meaningful startup equity
Catered lunches and dinners
Commuter benefit
Team-building events
Health, vision, and dental coverage
Flexible PTO
Latest Apple equipment
401(k) plan with match

About the Company

Eventual is building a video-native index on top of its distributed data engine, Daft, purpose-built for multimodal AI.
Their open-source engine is used by major companies like Amazon and FAANG.
The company aims to close the gap in data platforms for AI training, enabling faster iteration loops.
Eventual has raised $30M from prominent investors.
The team consists of experienced professionals from companies like AWS, Render, Pinecone, and Tesla.