Data Annotator
2 - 5 years
United States
Full-time
Remote
1 month ago
About the role
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
Responsibilities
Qualifications
Required
Preferred
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
Skills
EngineeringSoftware Development