Language Model Trainer

Innodata Inc. · India

Job Title: AI Language Model Trainer (Freelance/Remote)

Job Overview

We are seeking an Advanced English Specialist to join our team as a freelance AI Language Model Trainer. In this role, you will be responsible for evaluating, refining, and training cutting-edge Large Language Models (LLMs). You will challenge AI outputs on semantic precision, syntactic logic, stylistic nuance, and pragmatic alignment to ensure our models communicate with human-like accuracy.

This is a fully remote, flexible, project-based freelance opportunity compensated at a competitive hourly rate .

Key Responsibilities

Evaluate & Benchmark: Analyze complex model outputs, rating them against strict linguistic rubrics for factuality, tone, coherence, and stylistic fluidity. Prompt Engineering: Design adversarial prompts ("red-teaming") to stress-test the model's guardrails, logic, and edge-case handling. Linguistic Annotation: Correct subtle errors in syntax, semantics, and register variation, providing clear written rationales for model adjustments. Reinforcement Learning (RLHF): Synthesize high-quality data paths to train reward models on advanced text generation.

Qualifications & Requirements

Linguistic Mastery: Exceptional, native-level command of the English language with a deep understanding of rhetoric, advanced grammar, and style guidelines. Analytical Mindset: Ability to spot minute inconsistencies, logical leaps, or factual errors in AI outputs that an average reader would miss. Technical Comfort: Prior experience with LLMs, prompt engineering, or data annotation platforms is highly preferred but not mandatory. Independence: Self-motivated freelancer capable of managing their own hours while consistently hitting quality and accuracy metrics.

Project Details & Compensation

Employment Type: Freelance Contract / Project-Based Location: 100%

Remote Compensation: Competitive Hourly Rate (paid out based on approved logged task hours)

Hours: Flexible, depending on project volume.

Hiring & Selection Process

We maintain a strict quality threshold for our training data. Our vetting process consists of the following structure:

Initial Review: Verification of your linguistic background and profile details. Assessment Phase (Mandatory):Test 1: Core Linguistic & Logic Evaluation (Approx. 1.5 Hours)

Test 2: Practical Model Rating & Prompt Design Simulation (Approx. 1.5 Hours)

Note: The total vetting assessment time across both tests is roughly 3 hours

Onboarding: Only candidates who successfully clear both assessments with our benchmark score will be onboarded onto the active freelance project r oster.

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ta.com”