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Data Annotator
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Indeed
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79Q22222+22
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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.

Fuentea:  indeed Ver publicación original
Valentina Rodríguez
Indeed · HR

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Indeed
Valentina Rodríguez
Indeed · HR
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