Unbox is a testing and debugging platform for machine learning models. Unbox makes it easy for ML teams to find failures and biases, figure out their root causes, and create unit tests to ensure they stay fixed — all baked in with experiment tracking and versioning (think GitHub for ML). The company was founded by three previous Siri engineers who contributed to over 15 different AI/ML projects at Apple.
Unbox is currently working with several well-known enterprise companies worth over $1B, helping them rapidly improve the quality of their models and datasets and save tons of time and money.
We're looking for a founding engineer to help us build the future of sustainable, performant, and ethical machine learning.
We're backed by Y Combinator and several of the top investors and funds in the world, including the founders of companies like Instagram, Voyage, Instacart, Sendbird, Mercury.
- Design, build & ship user-facing features
- Improve & expand on components of the frontend architecture, from data & network to UI
- Incorporate customer feedback to improve the core product's UI/UX
- Establish & maintain excellent engineering standards through code review, Agile workflows, etc.
- 2+ years of software engineering experience
- (Optional) Bachelor’s degree (or equivalent)
- (Optional) Experience with data visualization web frameworks such as d3.js, Vega, etc.
- (Optional) Previous experience working on large-scale web application(s)
We offer highly competitive cash, equity packages, and benefits. The founding team works flexibly in and out of the office. Remote work is also a possibility.
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status, or other protected classes.
- Typescript + React Hooks with Redux for state management
- Built for Electron & web
- Flask + SQL (Postgres) + RQ workers for long-running tasks. We are deployed on AWS but offer a Dockerized cloud-agnostic version of the product. Several SoTA ML models used to generate insights and data-centric tests.