We’re looking for a Data Annotator (AI Training & Annotation) to support large-scale AI training projects focused on conversational data. You’ll work on detailed annotation and labeling tasks that help improve machine learning models — turning real, anonymized human conversations into structured datasets used to train next-generation AI.
This role is ideal for someone who’s detail-oriented, tech-savvy, and curious about how AI systems learn from human input. You’ll be part of a small, focused team working at the intersection of AI, data privacy, and voice technology.
🎁 Perks & Benefits
- 💵 Paid in USD, every 15th & 30th of the month
- 🏖️ Up to 14 days of Paid Time Off annually (starting Day 1)
- 📅 Observance of Holidays based on your location
- 🏡 100% remote – work from anywhere with reliable internet
- 🧠 Gain hands-on experience in AI data operations and machine learning pipelines
- 🚀 Be part of a company redefining how users own and profit from their data
🧩 What You’ll Be Doing
🎧 Annotation & Labeling
- Listen to recorded, anonymized voice data and accurately label key components such as intent, sentiment, or conversation type.
- Tag and categorize speech segments following specific project guidelines.
- Conduct data quality reviews to ensure accuracy, clarity, and consistency across annotations.
🧠 AI Training Support
- Contribute to building training datasets for natural language processing (NLP) and speech recognition models.
- Collaborate with the QA and engineering teams to clarify labeling logic and improve annotation tools.
- Provide feedback on data irregularities, unclear prompts, or edge cases to refine future project criteria.
📊 Documentation & Process Optimization
- Maintain clear labeling logs and progress reports.
- Follow and update annotation guidelines as project requirements evolve.
- Suggest process improvements or automation opportunities to boost efficiency.
✅ Who You Are
- 2+ years of experience in data labeling, annotation, or AI training support.
- Comfortable working with audio, text, image, or video data.
- Strong attention to detail and commitment to high-quality output.
- Familiarity with annotation platforms or labeling tools (e.g., Labelbox, Scale AI, Dataloop).
- Fluent in English (verbal and written), with solid comprehension of conversation nuance and tone.
- Self-motivated, dependable, and able to meet tight deadlines.
Bonus Points
- Prior experience labeling speech, transcription, or NLP datasets.
- Background in linguistics, AI, or data operations.
- Experience with OCR or multimodal data labeling.
📩 How to Apply
Please submit:
- ✅ Your updated resume
- ✅ A short Loom video (1–2 mins) introducing yourself and describing your experience with data labeling or AI training projects
🧠 If you’re fascinated by how human data trains intelligent systems and want to help shape the next generation of conversational AI, we’d love to hear from you.
📩 Application Process Overview
Our comprehensive selection process ensures we find the right innovative fit:
- Initial Application - Submit your application and complete our prequalifying questions
- Video Introduction - Record a brief video introduction showcasing your communication skills and work experience
- Role-Specific Assessment - Complete a homework assignment tailored to the position (if applicable)
- Recruitment Interview - Initial screening focusing on technical skills and innovation mindset
- Executive Interview - Discuss role alignment, experimentation approach, and career goals
- Client Interview - Final interview covering workflow integration and team collaboration
- Background & Reference Check - Professional reference verification
- Job Offer - Successful candidates receive a formal offer with a competitive compensation package
We provide feedback at each stage and maintain transparent communication throughout the process.
