Remote Audio Annotation Specialist (AI Training) - 33328

Turing; Canada; Remote; CAD 30,000 - 60,000; Full time

Job summary

Turing is seeking entry-level Audio/Voice/Annotation Trainers to support the development of large language models (LLMs). The role involves recording audio samples and annotating voice data, contributing to the understanding of AI systems. This is a 100% remote position, ideal for candidates with strong English skills and attention to detail who can work collaboratively and independently.

Benefits

Work Remotely

Competitive Compensation

Collaborate with Experts

Skill Building

Qualifications

• Strong skills in reading, writing, and speaking English.
• Comfort with a variety of regional accents.
• Ability to follow nuanced instructions.

Responsibilities

• Record high-quality audio by reading scripts clearly.
• Annotate and label voice data for AI model training.
• Deliver accurate outputs across large volumes of tasks.

Skills

English Proficiency

Attention to Detail

Tech-Friendly

Analytical Mindset

Communication

Self-Starter

Job description

2 days ago Be among the first 25 applicants

Turing is an AI-powered tech services company with a mission to accelerate AGI advancement and deployment by bridging the gap between global talent from 100+ countries and the world's best foundational LLM companies by helping them improve performance through model evaluation, fine-tuning, feedback, factuality, and handling diverse data.

Role Overview

A leading US-based technology company is seeking skilled individuals with strong English proficiency and clear verbal communication to join a cutting-edge AI project as Audio/Voice/Annotation Trainers. This role supports the development of large language models (LLMs) by recording audio samples, annotating voice data, and ensuring accuracy and consistency in accordance with project guidelines.

This is a unique opportunity to shape the future of AI systems' understanding of voice, intonation, and pronunciation—while working with some of the most innovative LLM teams in the industry.

Key Responsibilities:

• Record high-quality audio by reading scripts and prompts clearly and consistently.
• Annotate and label voice data for use in supervised AI model training.
• Deliver accurate, consistent outputs across large volumes of tasks.
• Share feedback to help refine prompts and instructions.
• Work closely with QA and project leads to ensure annotation quality.

Requirements:

• English Proficiency: Strong skills in reading, writing, and speaking.
• Accent Familiarity: Exposure to and comfort with a variety of regional accents.
• Attention to Detail: Ability to follow nuanced and specific instructions.
• Tech-Friendly: Comfortable using basic computer tools and handling audio files.
• Analytical Mindset: Able to grasp context and intent behind scripts.
• Communication: Professional and responsive in a remote, collaborative environment.
• Self-Starter: Able to work independently with minimal supervision.
• Availability: Ideally 20+ hours/week.
• Location: Must reside in the US or US Territories.
• Timezone Overlap: Availability for 2–5 hours/day overlap with UTC-8:00 (PST) may be required.
• Equipment: Reliable computer, good-quality microphone, and stable internet connection.

Nice to Have:

• Experience in voiceover, podcasting, transcription, or linguistics.
• Familiarity with annotation tools or audio editing software.
• Access to high-quality recording equipment.
• Work Remotely: 100% remote, flexible work setup.
• Competitive Compensation: Fair and attractive pay for your time and skills.
• Collaborate with Experts: Work alongside top-tier teams in AI and language technology.
• Skill Building: Hands-on experience with state-of-the-art LLM training processes.

Note: Shortlisted candidates may be required to complete a coding assessment as part of the selection process.

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Contract

Job function

• Job function

  Information Technology

• Industries

  Software Development

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