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AI Data Labeling Analyst

Remote / Online - Candidates ideally in
Anaheim, Orange County, California, 92801, USA
Listing for: EPITEC
Remote/Work from Home position
Listed on 2026-11-01
Job specializations:
  • IT/Tech
    AI Business & Operations, Data Analyst, Data Scientist
Salary/Wage Range or Industry Benchmark: 50000 - 80000 USD Yearly USD 50000.00 80000.00 YEAR
Job Description & How to Apply Below
Job Title:

AI Data Labeling Analyst

Location:

Open For 100% Remote Job(US Only)

12 months contract(With Possibility Of extension)

W2 Only

Required Qualifications

5-7 years in operations, program management, analytics, consulting or applied AI, where you were responsible for results.

Job Title:

AI Data Labeling Analyst

Location:

Open For 100% Remote Job(US Only)

12 months contract(With Possibility Of extension)

W2 Only

Required Qualifications

5-7 years in operations, program management, analytics, consulting or applied AI, where you were responsible for results.

You use AI every day and have built something with it that has actually moved the needle, such as a workflow, an automation or an analysis. You know where it breaks, and you keep pushing it further.

You're comfortable with numbers: accuracy, precision and recall, sampling. SQL and notebooks help. If you haven't used them yet, you'll pick them up quickly with AI assistance.

You're curious about how work actually gets done, including the awkward exceptions, and you've taken a messy process and made it measurable.

You've worked on quality in some form, such as review guidelines, QA or audits.

You write clearly and can work with business leads, PMs and engineers in the same week.

You're fine working with limited direction, and you try things yourself instead of waiting for someone to build them. A technical background isn't required.

You don't need to have designed evaluations or calibrated LLM judges before. We'll teach you, and you'll work with a team that has done it many times.

Preferred Experience

Hands-on SQL, Python or API experience.

Trust and safety, content moderation, annotation operations or other human-in-the-loop work at scale.

Fine-tuning models or calibrating LLM judges.

Background in a two-sided marketplace, travel, or another operations-heavy business.

Experience setting up intake and prioritization for a new team.

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