Scale AI

Currently our Engineering team is roughly 30 total. Our major departments, as of now, are Data Science/Machine Learning, Frontend (Applications and UI), Backend (generalist, Infra, DevOps) and QA. The teams each have a TL/Manager which you would report to for weekly checkins an d1:1s. Each department has sub teams that have daily standups, project planning, and cycles of execution for production. Every week, there is an entire EPD (engineering, product and design) standup where each team shares the State-Of-The-Union. On Fridays, we have engineering demos, open to all engineers to share what they've been working on with the rest of HQ. This is a great chance to give some insight into our non-technical employees and to provide more context around the work that's going on!

1) We're effectively building Amazon Web Services for people. We provide our customers with a statistically guaranteed high quality of service, making sure we're routing incoming tasks to the correct place and assigning the best possible people to each task.

2) We need to build new Machine Learning models to make the process of solving tasks more efficient. We've built products that integrate ML model outputs with human QA and need to continue developing new models as well as building the backend architectures and user interfaces that best combine humans and ML.

3) We have a lot of customer facing software to build, e.g. building more tools into the customer dashboard, improving API design, client libraries, etc.

4) On our backend we have many challenges to improve the routing of tasks to scalers (people completing the incoming tasks), building systems to staff and de-staff scalers based on their quality over time.