Staff / Principal Research Scientist
Inworld AI develops AI products for growing applications, helping developers go from prototype to production faster. Their offerings include advanced text-to-speech (TTS) technology and an upcoming Runtime product, aimed at enhancing consumer applications with expressive, real-time voice AI.
Maintainer signals as of 8/23/2026
Funding history
About Inworld AI
Inworld develops AI products for consumer applications. They offer a text-to-speech model that aims for high quality with better pricing, lower latency, more control, local serving options, and open training code. They also have a product called Inworld Runtime, which is currently in private preview. Their services are used by partners like XBOX, Ubisoft, NVIDIA, and Meta. They focus on helping developers go from prototype to production faster and increase experimentation velocity to deploy new AI improvements daily.
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
