Staff / Principal Research Scientist
Inworld AI is a research lab and inference provider for realtime AI at consumer scale. It provides text-to-speech, speech-to-text, speech-to-speech, and LLM routing products for developers and businesses building consumer-facing applications.
Maintainer signals as of 9/25/2026
Funding history
Projects
About Inworld AI
Inworld AI develops and operates realtime AI infrastructure, including first-party text-to-speech and speech-to-text models, a customizable speech-to-speech Realtime API, and an LLM Router that routes requests across leading model providers. Its platform supports voice agents, social and companion applications, learning and education, health and wellness, agentic workforce applications, and games and media. The company serves developers, businesses, and teams building consumer-facing applications.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Join Inworld's research lab building realtime voice models. Frame research questions, run experiments, ship results, treat evaluation as a first-class research product, and collaborate with US-based leadership and engineering teams.
Requirements
- Experience with foundation models including training, new architectures, reinforcement learning, reward modeling, and scaling
- Experience with evaluation including benchmarks, evaluation loops, quality measurement, LLM-as-judge, and failure analysis
- Experience with frontier topics such as multimodal models, agents, tool use, test-time compute, or world models
- Published research at ICML, ICLR, NeurIPS, EMNLP, ACL, or AAAI
- PhD in ML/NLP or equivalent practical experience
- Public work such as non-trivial AI side projects, interdisciplinary experiments, or open-source contributions
- Full-stack research ownership experience
- Professional fluency in English, written and spoken
- Legal right to work in Switzerland
Responsibilities
- Frame research questions and run experiments
- Design evaluation loops and quality measurement systems
- Conduct failure analysis on models and systems
- Own research end-to-end from question framing to shipped result
- Collaborate daily with US-based leadership and engineering teams