Software Engineer, Product
About The Position
Eventual is building the data engine for Physical AI, designed to handle the massive multimodal datasets required for training advanced AI systems like humanoid robots and autonomous vehicles. Current data platforms are not optimized for this type of data, leading to slow iteration cycles for AI teams. Eventual's open-source engine, Daft, is purpose-built for multimodal AI and is already processing petabytes of data daily at major companies. The company is developing a video-native index to accelerate the data iteration loop for Physical AI researchers, enabling them to describe their data needs and receive curated datasets quickly. Eventual has raised $30M from prominent investors and has a world-class team from leading tech companies. They are looking for passionate individuals to join their small, powerful team working 4 days a 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
- 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
