English (US) AI Voice Trainer at Inworld

Inworld is an artificial intelligence research and infrastructure company specializing in real-time AI technologies for consumer-facing applications.

The company develops its own speech models, provides large language model (LLM) services, and powers AI inference through modular APIs built to support high-volume, real-time applications.

Every day, hundreds of millions of users interact with applications powered by Inworld, with the company processing more than 10 trillion LLM tokens monthly.

Its technology and infrastructure support a wide range of consumer applications across industries such as healthcare, fitness, education, entertainment, digital companions, and media.

Inworld’s work encompasses advanced AI research, real-time inference, large-scale infrastructure, and developer-focused APIs that enable businesses to integrate intelligent AI capabilities into their products and services.

The company has raised over $125 million in funding from prominent investors, including Lightspeed Venture Partners, Section 32, Kleiner Perkins, Microsoft’s M12 venture fund, Founders Fund, Meta, and Stanford, among others.

Its technology has supported leading organizations and products, including NVIDIA, Microsoft Xbox, Niantic, Logitech Streamlabs, Wishroll, Little Umbrella, and Bible Chat.

Inworld has also earned industry recognition from CB Insights as one of the world’s 100 most promising AI companies and was named among LinkedIn’s Top 10 Startups in the United States.

Position Summary

Inworld is seeking a skilled and detail-oriented AI Voice Trainer to help evaluate, assess, and improve the quality of its advanced speech technologies.

The successful candidate will play an important role in ensuring AI-generated voices sound natural, expressive, accurate, and consistent with their intended instructions.

This position involves reviewing audio samples, evaluating voice characteristics, assessing cloned voices, testing new speech features, and providing structured feedback to support continuous improvements in AI voice models.

Key Responsibilities

• Listen to paired or grouped speech recordings and determine which samples demonstrate better naturalness, expressiveness, and adherence to instructions.
• Evaluate AI-generated voices using established assessment criteria covering clarity, emotional expression, pronunciation, pacing, and overall delivery.
• Identify and categorize voice characteristics, including perceived gender, age range, accent, dialect, and speaking tone, while identifying inconsistencies in existing metadata.
• Assess the accuracy and similarity of cloned voices by comparing generated speech against the original speaker’s recordings.
• Review collections of newly developed voices to evaluate audio quality, consistency, and suitability before public release.
• Test new speech features in pre-release environments and identify technical issues, unusual behaviors, and potential usability improvements.
• Prepare clear, detailed evaluation reports and actionable recommendations that help engineering teams improve voice models.
• For multilingual assignments, assess pronunciation accuracy, dialect consistency, and natural speech delivery in the relevant native language.

Qualifications and Requirements

• Professional training or experience in audio production, broadcasting, voice acting, music, linguistics, phonetics, or a related discipline.
• Excellent listening skills, with the ability to recognize and describe subtle differences in pronunciation, speech rhythm, timing, prosody, and audio quality.
• Strong attention to detail and the ability to maintain consistent evaluation standards when reviewing large volumes of similar audio samples.
• Comfortable working with web-based testing platforms, VPN connections, spreadsheets, and basic troubleshooting procedures.
• Strong written English communication skills, particularly when documenting observations and providing structured feedback.
• Ability to complete assigned tasks within short turnaround times, sometimes within 24 hours.
• Flexibility to accommodate occasional weekend assignments when required.

Preferred Qualifications

• Native or near-native fluency in Hindi, Tamil, Telugu, Bengali, Marathi, Brazilian Portuguese, or a regional Spanish dialect.
• Previous experience working with text-to-speech (TTS) systems, voice AI technologies, dubbing, or localization quality assurance.
• Familiarity with A/B testing, audio evaluation, data annotation, or AI model assessment workflows.