In machine learning, data curation is only part of the battle to create a successful model. Once a model is trained, it needs to be tested and evaluated for performance. A model may perform well at predicting one particular type of classification, but struggle on another. This can occur due to a variety of factors, including poorly labeled or missing training data of specific classifications.
At Labelbox, the Active Learning team’s mission is to build products and workflows to surface insights into model performance after completing the training process. We seek to give machine learning engineers and data scientists the tools they need to validate models against ground truth data, spot model inaccuracies, identify gaps in cohorts of training data, and initiate workflows to improve that data.
About the Role
As a senior backend engineer on the SDK team, you will work with fellow engineers and product managers to design and build the interfaces and experiences that our users leverage to programmatically accomplish their workflows within Labelbox. You will seek to understand the current workflows of data scientists and machine learning engineers, and design elegant and easy to use public API’s to accomplish those goals. You will design and build scalable and flexible systems to automate the processing of large quantities of data to surface valuable insights. You will be expected to utilize the full range of design, modeling, and execution skills to create useful and performant interfaces for our products and customers.