Data Annotator
Jobright.aiFull Description
Jobright is a next-generation AI job search platform built to make career navigation faster, smarter, and more personal. They are looking for a Data Annotator to build the high-quality datasets that train, evaluate, and continuously improve the AI agents at the heart of our product.
Why Join Us
* Shape the data that directly determines how well our AI agents perform for millions of job seekers
* See the impact of your work in agent quality metrics within days, not quarters
* Learn from applied AI engineers and researchers who treat annotation as a core part of model development, not an afterthought
Responsibilities
* Label, review, and refine datasets across resumes, job descriptions, and agent conversations that train and evaluate the AI agents
* Apply detailed annotation guidelines with consistency and judgment, flagging edge cases and ambiguity so the team can sharpen the rules over time
* Partner with applied AI engineers and researchers to surface patterns in model errors, suggesting where targeted data work could most improve agent quality
* Help build and refine annotation guidelines, quality checks, and review workflows so the team's data operations get better as we scale
Qualifications
Required
* Recent grad or early-career professional with 0 to 2 years of experience in data annotation, content review, research, or a related field
* Strong communicator who can explain labeling decisions clearly and ask sharp questions when guidelines run out
* Sharp attention to detail and good judgment in ambiguous cases, with a working understanding of how training data shapes AI and machine learning systems
* Must be based in and authorized to work in the United States
Preferred
* Internship or project experience in data annotation, linguistics, qualitative research, or content operations at a tech or AI-focused organization
* Demonstrated ability to maintain high accuracy and throughput while working through large volumes of nuanced material
* Familiarity with annotation tools, basic SQL or spreadsheet analysis, and comfort working with LLM outputs and prompt-based workflows