AI Tutor & Domain Expert
Domain experts apply specialized knowledge to strengthen AI systems through hands-on work in data annotation, model evaluation, and training refinement. These professionals leverage deep expertise in specific fields—from psychology and audio engineering to business operations and customer support—to create high-quality training datasets and provide critical feedback that shapes how AI models behave. They work closely with technical teams to translate real-world problem-solving into actionable data that improves model reasoning, accuracy, and domain-specific performance. What distinguishes this work is the direct expertise requirement; practitioners must combine genuine mastery in their subject area with the ability to decompose complex problems into trainable signals for AI systems. These roles typically sit within dedicated human data or training teams at AI companies, collaborating with machine learning engineers and product teams to ensure models learn nuanced, accurate representations of their domains.
Skills
What companies are looking for in this role.
Labeling and annotating machine learning training data with high precision and consistency
Evaluating and ranking model outputs against quality criteria and guidelines
Auditing and correcting text outputs to improve model performance
Applying nuanced domain expertise to assess complex or ambiguous content
Developing and maintaining annotation schemas and standard operating procedures
Identifying edge cases, gaps, and patterns in annotation data to improve schema coverage
Training and onboarding annotators to ensure consistency across teams
Advising on domain-specific logic and establishing benchmarks for professional integrity
Designing domain-specific evaluation benchmarks and test datasets
Translating expert-level intuition into rigorous, computable frameworks for model evaluation
Conducting red teaming and safety testing on language model outputs
Collecting and generating high-quality motion or behavioral data for training AI systems
Contributing to research publications and technical reports on AI evaluation methodologies
Working independently with high attention to detail and consistent decision-making
Maintaining meticulous attention to detail and quality standards across repetitive tasks
Demonstrating strong contextual judgment and cultural sensitivity when evaluating content
Providing detailed, actionable feedback to technical teams on model behavior and data quality
Communicating complex domain knowledge clearly to cross-functional teams
Collaborating with researchers and engineers to refine annotation tools and workflows
Rapidly mastering new physical tasks and finding optimal execution methods
Technology
The tools and technologies that define this role.
Open Jobs
82 open AI Tutor & Domain Expert jobs across 15 companies.
Other Research & Science roles
Scientists conducting original research to advance the state of the art in AI, machine learning, and related fields.
Engineers who build the systems, tools, and infrastructure that enable research.
Senior individual contributors at AI labs working on core model development, pre-training, post-training, and model optimization.
Leaders who manage research teams, set research agendas, and guide scientific strategy.
Scientists who apply machine learning techniques to solve specific product or domain problems.