About the role
About Cartesia Our mission is to architect AI that learns from and interacts with the world like humans do. We're pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences. We're funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We're fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world's foremost experts in AI.
About
the Role We are looking for a Transcription Operations Manager to establish a transcription workflow across 30+ different locales. You will act as the single accountable owner for this critical pipeline, driving end-to-end execution from hiring and training annotators to partnering with our engineering team on tooling. Your Impact Own day-to-day transcription operations, successfully delivering ground truth transcripts for 30+ locales. Oversee the entire annotator lifecycle: hiring, onboarding, training, calibration, and ongoing performance management. Create robust training materials, quizzes, and instructions to ensure annotators meet our exact standards. Audit annotator work continuously, providing highly detailed feedback to ensure data integrity. Partner closely with the Engineering and Product teams to coordinate
requirements and iterate on our internal transcription tools. What you bring Strong project management and operational execution skills—you know how to build a process from scratch and see it through to completion. Experience managing and calibrating distributed teams, contractors, or annotators. A systems-thinking mindset with the ability to translate manual workflows into product/tooling
