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The AI Trainer will evaluate and score speech samples for naturalness, clarity, and emotional expression while labeling voice attributes. They will also test new speech features, report bugs, and provide structured feedback to engineering teams.
About Inworld
Inworld is a research lab and inference provider focused on realtime AI for consumer-facing applications. We build first-party speech models, serve LLMs, and run the inference behind modular APIs designed for high-volume, realtime workloads.
Hundreds of millions of users interact with Inworld powered apps every day and we serve over 10 trillion LLM tokens per month. Our models and infrastructure support consumer applications across companions, healthcare, fitness, education, media, and more. Our work spans model research, realtime inference, large-scale serving infrastructure, and the APIs developers use to bring these capabilities into production.
We’ve raised more than $125M from Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, Stanford, and others. Our technology has powered experiences from companies including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat. Inworld has also been recognized by CB Insights as one of the 100 most promising AI companies globally and named one of LinkedIn’s Top 10 Startups in the USA.
Listen to paired or grouped speech samples and judge which sounds more natural, expressive, or faithful to instructions
Score voices against rubrics for naturalness, clarity, emotion, pacing, and delivery style
Label voice attributes such as perceived gender, age, accent or dialect, and tone, and flag mismatches with existing metadata
Judge how closely cloned voices match their source speaker
Review batches of new voices for audio quality and suitability before public release
Test new speech features in pre-release environments and report bugs, edge cases, and usability issues
Write clear, structured findings that engineers can act on
For multilingual roles: evaluate pronunciation, dialect accuracy, and naturalness in your native language
A trained ear. Background in audio production, broadcast, voice acting, music, linguistics, phonetics, or similar
Ability to hear and describe subtle differences in prosody, timing, pronunciation, and audio quality
Consistent, careful judgment across large batches of similar samples
Comfort with beta web tools, VPN access, and spreadsheets, and willingness to troubleshoot minor access issues
Strong written English for reporting findings
Ability to turn tasks around within a day when needed, including occasional weekend availability
Native or near-native fluency in Hindi, Tamil, Telugu, Bengali, Marathi, Brazilian Portuguese, or a regional Spanish dialect
Experience with TTS, voice AI, dubbing, or localization QA
Familiarity with A/B evaluation or annotation work
Location: Remote within the United States.
Compensation: $20-$55 per hour. Rate depends on region and language specialty.
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