The future of AI — whether in training or evaluation, classical ML or agentic workflows — starts with high-quality data.
At HumanSignal, we’re building the platform that powers the creation, curation, and evaluation of that data. From fine-tuning foundation models to validating agent behaviors in production, our tools are used by leading AI teams to ensure models are grounded in real-world signal, not noise.
Our open-source product, Label Studio, has become the de facto standard for labeling and evaluating data across 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’s the most widely adopted OSS solution for teams working on building AI systems.
Label Studio Enterprise builds on that traction with the security, collaboration, and scalability features needed to support mission-critical AI pipelines — powering everything from model training datasets to eval test sets to continuous feedback loops.We started before foundation models were mainstream, and we’re doubling down now that AI is eating the world. If you're excited to help leading AI teams build smarter, more accurate systems — we’d love to talk.
Software Engineering Intern - AI Data Operations
HumanSignal | Columbus, Ohio | Hybrid | Spring/Summer 2026
About Us
HumanSignal builds Label Studio Enterprise, the data annotation platform trusted by Fortune 500 companies including Apple. We're expanding our 400+ person Columbus facility and need engineering talent to build systems that power AI training pipelines.
What You'll Build
- Full-stack web applications for crowdsourced data collection with quality control workflows
- Admin dashboards with bulk operations, analytics, and workflow management
- Data pipelines integrating Label Studio, AWS S3, and automated quality checks
- JSON transformation systems processing thousands of annotation files for enterprise clients
Technical Skills (Strong in Several Required)
- Frontend: React, TypeScript, responsive UI, state management
- Backend: Python (data processing, APIs, automation), RESTful design
- Data: Database design, JSON manipulation, multi-status workflows
- Deployment: Vercel, serverless functions, CI/CD
Bonus: AWS S3, email integration, real-time updates, admin dashboards
Who You Are
- Ohio State engineering student (CS, Software Engineering, Data Science, or related)
- Can architect solutions and ship working code autonomously
- Comfortable with full-stack development and data pipelines
- Interested in AI infrastructure and training data systems
Details
- Location: Hybrid in Columbus (2-3 days/week in-office)
- Compensation: $35-50/hour based on experience
- Schedule: Flexible part-time or work-study arrangements
- Duration: Minimum 12 weeks, potential for extension/conversion
To Apply
Email resume, GitHub, and brief note to [email protected] including:
- A technical challenge you've solved with data or workflows
- Your availability and preferred start date
HumanSignal is committed to building a diverse team. We encourage applications from candidates of all backgrounds.
We're moving fast—strong candidates will be interviewed on a rolling basis.
What We Do
HumanSignal (formerly known as Heartex) enables data science teams to build AI models with their company DNA. With the emergence of generative AI, it’s more important than ever to build highly differentiated models by guiding foundation models with proprietary data and human feedback. Creators of Label Studio, the most popular open source data labeling platform, HumanSignal enables data scientists to develop high quality datasets and workflows for model training, fine tuning and continuous validation. Today, the Label Studio open source community has more than 250,000 users who have collectively annotated more than 100 million pieces of data. Label Studio Enterprise is available as a cloud service with enhanced security, automation, quality review workflows, and performance reporting, used by leading data science teams including Bombora, Geberit, Outreach, Wyze, and Zendesk.
