Jobs at Expand AI

Training data is what powers machine learning algorithms in this age of machine learning and AI. Yet, the method used to produce high-quality training data is an area that is still highly underdeveloped and is a huge bottleneck that the ML pipeline is currently facing. Using human annotators to produce training data is what is commonly done. While this method helps produce accurate training data sets, it is immensely time-consuming and costly which is slowing the growth of ML applications. Moreover, the standard way of using crowdsourced labeling services becomes a problem for large companies where data is highly private and they respond to this through in-house teams to label data by bearing enormous costs. Additionally, tasks can change over time but hand-labeled data is static and cannot adapt to this change. Using a combination of mathematical and statistical models along with ML algorithms, Expand AI aims to pioneer the industry standard for data labeling by programmatically labeling data to produce high-quality, highly accurate training data sets at the lowest turn-around time. Using a program to label data also does away with privacy concerns and enables data to adapt to changing tasks. Being able to produce highly accurate training data sets at the lowest turn-around time will most importantly accelerate the growth of AI applications across various industries and in consumer tech products thus unleashing the full potential of ML and AI applications.