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Your profile is how employers find you and how the matching engine ranks you for jobs. A complete profile with specific labeling experience gets surfaced more often and to better-matched opportunities. You can access the profile wizard from Settings → Profile in your trainer dashboard. You can return to it any time to update your information.
1

Upload your resume

The first step uploads your resume so the platform can auto-fill your profile. Two resume types are supported:
  • General resume (required) — your overall work history and background
  • Data labeling resume (optional) — a separate resume focused on annotation, RLHF, or labeling-specific experience
Accepted formats: PDF, DOCX, or TXT — max 10 MB each.When you upload your general resume, the platform parses it and pre-populates your work history, education, skills, and contact details. You review and edit each section in the steps that follow.
If you upload a second resume later, the platform cross-checks it against your original to verify consistency. Significant mismatches may affect your profile status.
2

Add your basic details

Fill in your contact and location information:
  • Full name
  • Country — used for location-based job matching and payout eligibility
  • City
  • Phone number
  • LinkedIn URL — the platform normalizes your URL automatically
Your country determines which jobs you are eligible to apply for when an employer restricts their listing to specific locations.
3

Add your labeling experience

This is the most important section for job matching. For each project or role where you did AI training or annotation work, add an entry with:
  • Platform or tool used (e.g., Scale AI, Labelbox, CVAT, Appen, Remotasks, or internal tooling)
  • Data types you worked with — image, video, text, audio, document, code, 3D sensor, medical, geospatial
  • Label types you performed — bounding box, polygon, segmentation, classification, NER, RLHF, fine-tuning, SFT, red-teaming, transcription, evaluation/rating, and more
  • Duration and dates
Add a separate entry for each platform or tool you have used, even if the work overlapped in time. Employers often filter by specific software, and having each tool listed individually improves your match quality.
4

Set your skills

The skills section captures three dimensions that the matching engine uses:
  • Software tools — select every labeling or annotation platform you have hands-on experience with from the full list (Scale AI, Labelbox, Label Studio, Encord, Roboflow, AWS SageMaker, etc.)
  • Data types — the types of data you are comfortable annotating
  • Label types — the annotation and training task types you can perform
These overlap with your labeling experience entries but apply platform-wide across all your work, not just a single project.
5

Add work experience

Add your general professional work history — roles, companies, dates, and descriptions. The resume parser auto-populates these from your uploaded resume, but you can add, edit, or remove entries manually.This section is separate from labeling experience and covers non-AI-training roles in your background.
6

Add education

Add your education history — school, degree, field of study, and graduation year. The resume parser auto-populates these as well.
7

Set your rate and availability

Set your hourly rate and weekly availability. Availability options are:
  • Less than 20 hrs/week
  • 20+ hrs/week
  • I don’t know yet
Experience level options (used for job matching):
  • Entry Level — less than 1 year of AI training experience
  • Intermediate — 1–3 years
  • Expert — 3+ years of data labeling or annotation experience
8

Set up your public profile

Configure your public-facing profile:
  • Profile photo — upload a photo to display on your profile and proposals
  • Profile title — a short headline that appears on your public profile
  • Profile slug — your custom public profile URL: app.opentrain.ai/<your-slug>
  • Profile visibility — control whether your profile is publicly discoverable
Your profile slug must be unique. Once set, your public profile is accessible to anyone with the URL, including employers who discover you outside the platform.
9

Review and submit

The final step shows a summary of everything you have filled in. Review each section and go back to correct anything before submitting.Once you submit your profile, it is added to the matching pool and you can start applying to jobs.

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Languages

Add the languages you speak and your proficiency level for each (Native/Bilingual, Fluent, Conversational, or Basic). Language is a primary matching factor for many jobs — especially translation, localization review, and multilingual annotation work.

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Agency onboarding

If you represent a team of labelers rather than working solo, use the Agency onboarding flow from your dashboard. This creates a company-level profile that covers your team’s headcount, security and compliance credentials, and pricing. Agency accounts have access to subscription plans that control job visibility and the number of team members who can apply. The Free plan has restricted access — upgrade to Basic or Pro to unlock the full job feed.
Even as an agency, individual team members should complete their own trainer profiles. Employer proposals and contracts are tied to individual accounts.