About the job
The future of AI , whether in training or evaluation, classical ML or agentic workflows , starts with high-quality data.
At HumanSignal, we’re developing a cutting-edge platform that facilitates the creation, curation, and evaluation of high-quality data. Our tools empower leading AI teams to fine-tune foundation models and validate agent behaviors in production, ensuring models are grounded in real-world signals rather than noise.
Our open-source product, Label Studio, has established itself as the de facto standard for labeling and evaluating data across various modalities , from text and images to 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 open-source solution for teams focused on building AI systems.
Label Studio Enterprise extends this success by offering the security, collaboration, and scalability features essential for mission-critical AI pipelines, supporting everything from model training datasets to evaluation test sets and continuous feedback loops. We began our journey before foundation models gained popularity, and we are committed to innovating as AI transforms industries. If you’re excited to help leading AI teams create smarter, more accurate systems, we’d love to hear from you.
HumanSignal is on the lookout for an Operations Specialist to bolster our delivery teams as we scale operations for our Label Studio platform and Data Creation Laboratories. In this role, you will serve as a vital support system for delivery leads managing intricate data projects for pioneering AI labs and enterprise clients. You will connect technical operations with project execution, ensuring the seamless delivery of purpose-built datasets that drive groundbreaking AI applications.
Our Data Creation Laboratories manufacture training data from the ground up in controlled environments , this goes beyond traditional data labeling. The technical intricacies of our deliverables require operators who grasp data architecture, can troubleshoot pipeline issues, and approach data flow systematically from creation to customer delivery. If you possess an engineering mindset and are eager to engage hands-on in one of the most exciting domains in AI, this role offers significant impact.
