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.
HumanSignal is seeking highly qualified software engineering and computer science experts to contribute to cutting-edge AI development projects. This role involves evaluating, annotating, and validating code across multiple programming languages and domains to improve AI model performance in software development and problem-solving.
CompensationUp to $110 USD/hour based on qualifications and project complexity
Required QualificationsEducation- Master's degree required in a computer science or software engineering-related field
- PhD strongly preferred in:
- Computer Science
- Software Engineering
- Computer Engineering
- Computational Science
- Information Science
- Or closely related technical disciplines
Candidates must hold degrees directly in computer science, software engineering, or computationally-intensive fields. Acceptable programs include:
- Computer Science
- Software Engineering
- Computer Engineering
- Computational Science
- Information Technology (with strong programming foundation)
- Data Science/Machine Learning
- Electrical Engineering (with software emphasis)
- Review and evaluate code for correctness, efficiency, and best practices
- Annotate code logic, algorithms, and implementation approaches
- Validate AI-generated code across various programming languages and frameworks
- Identify bugs, security vulnerabilities, and performance issues
- Provide detailed feedback on code quality, structure, and documentation
- Work with problems spanning algorithms, data structures, system design, and software architecture
- Deep understanding of software engineering principles across multiple domains
- Proficiency in multiple programming languages
- Strong analytical and problem-solving skills
- Excellent attention to detail and code quality standards
- Ability to clearly articulate technical reasoning and trade-offs
- Experience with version control, testing frameworks, and development tools
- Familiarity with software development methodologies
- Ability to work independently and meet deadlines
- Flexible, project-based work - work on your own schedule
- Remote position - work from anywhere
- Variable hours based on project availability and your capacity
- Ongoing training and calibration provided
- Quality-focused environment with performance feedback
- Active software engineers, researchers, professors, or recent graduates in CS/engineering fields
- Strong GitHub/portfolio or demonstrated technical expertise
- Experience in software development, research, or industry applications
- Passion for advancing AI capabilities in software development domains
Interested candidates should be prepared to:
- Submit CV/resume highlighting technical qualifications
- Provide proof of advanced degree(s)
- Complete a brief coding assessment
- Participate in a qualification review
Top Skills
HumanSignal San Francisco, California, USA Office
San Francisco, California, United States, 94103
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