About the job
The future of AI , whether in training or evaluation, classical ML or agentic workflows , hinges on the availability of superior data.
At HumanSignal, we are pioneering the platform that fuels the creation, curation, and evaluation of high-quality data. Our tools facilitate everything from fine-tuning foundational models to validating agent behaviors in production, empowering leading AI teams to ensure models are anchored in real-world signals rather than noise.
Our open-source product, Label Studio, has emerged as the de facto standard for labeling and evaluating data across various modalities , encompassing text, images, time series, and agents in environments. With over 250,000 users and hundreds of millions of labeled samples, it stands as the most widely adopted OSS solution for teams dedicated to building AI systems.
Label Studio Enterprise builds on this momentum by incorporating the security, collaboration, and scalability features essential for supporting mission-critical AI pipelines , from model training datasets to evaluation test sets and continuous feedback loops. As we advance in an era where AI is reshaping industries, we are excited to invite candidates who are eager to assist premier AI teams in constructing smarter and more accurate systems.
We are looking for a Quality Operations Lead to uphold exceptional data quality across our Label Studio platform and Data Creation Laboratory operations. In this pivotal role, you will serve as the ultimate authority on the integrity and utility of the data we create and deliver to our clients. You will lead accountability across our most impactful projects, addressing complex quality challenges while spearheading strategic initiatives that ensure reliable and scalable delivery as we expand.
Our Data Creation Laboratories go beyond labeling existing data; we engineer purpose-built datasets from the ground up in controlled settings. This elevates the quality control process: you won’t just be verifying annotations; you will ensure that the human-generated data we produce meets the rigorous standards demanded by cutting-edge AI laboratories and enterprises pushing the boundaries of innovation.
