Software Engineer, Product
About The Position
Eventual is building a distributed data engine called Daft, purpose-built for multimodal AI, to address the limitations of current data platforms in handling the large datasets required for AI training. Their open-source engine is already in use at major companies like Amazon and Mobileye. Eventual aims to accelerate the AI development cycle by providing a video-native index that allows researchers to quickly describe, retrieve, and curate datasets for training. The company has raised $30M from prominent investors and has a team with experience from leading tech companies. They operate on a 4-day work week in their San Francisco office.
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, including 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 the cloud infrastructure underneath (AWS S3, etc.).
- Experience taking a product from ground zero to production — and the judgment to know when to take on tech debt for velocity vs. when to invest in extensibility.
- Bias toward shipping. You'd rather get a flawed v1 in front of a researcher today than spec a perfect v2 for next month.
Nice To Haves
- Experience building UIs over data — analytics dashboards, query builders, notebook environments, data exploration tools.
- Experience with video, image, or other multimodal content in the browser.
- Background in developer-facing or technical products, especially for ML/AI or data engineering audiences.
- Comfort with Python on the backend (our platform is Python/Rust).
- Worked closely with research or technical end users before.
Responsibilities
- Design and build the product UI for exploring, querying, and curating multimodal datasets — including video playback, clip-level annotation, and visualizations over corpus composition.
- Design and build the APIs that drive the UI and that customers integrate against from their own training stacks and notebooks.
- Build analytics that help researchers understand their corpus: distributions over labeled axes, dataset composition over time, query result quality, training-job dataset provenance.
- Work closely with the Visual Understanding, Dataloading, and Storage teams so the product surface stays a thin, fast layer over a deep platform.
- Sit with researchers at design-partner labs, gather requirements directly, and turn them into shipped features in days — not quarters.
- Write high-quality, extensible, maintainable code.
- Take on tech debt deliberately for velocity, and pay it down deliberately when the product proves out.
Benefits
- 4 days/week in our SF Mission office.
- Competitive comp and meaningful startup equity.
- Catered lunches and dinners for SF employees.
- Commuter benefit.
- Team-building events and poker nights.
- Health, vision, and dental coverage.
- Flexible PTO.
- Latest Apple equipment.
- 401(k) plan with match.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
