ML Engineer & Research Scientist, Speech (Full-time)

Voice Arena builds evaluations, models, and datasets for voice AI. The ML Engineer & Research Scientist will identify open problems in speech, define desired model behavior, develop evaluations and datasets, train models, and publish and open-source the resulting work.

Responsibilities:

• Identify the problems in speech. Find the gaps between today's speech models and machines that talk like humans, across recognition, synthesis, turn-taking, conversation, emotion, languages and accents. Listen to where models fail, read the literature, talk to the labs and users who hit these failures every day, and turn what you find into clear problem statements
• Define the behaviour we want models to have. For each problem, write down precisely how a model should behave: what a good response sounds like, what counts as a failure, and where the line between them sits. This becomes the target labs build towards
• Design the evals. Turn that behaviour into a measurement: test sets, automatic metrics, and human evaluation protocols where metrics fall short. Run current models through it and show where they stand and where they break
• Define the datasets. Specify the data that would teach models the missing behaviour: what to record, from whom, in which languages and conditions, and how to label it. Our operations team builds it to your spec, and you own its quality
• Train models on that data. Train and fine-tune models on the new data to prove it works. You'll be responsible both for making the numbers go up and for making sure the numbers mean something. The bar: models that climb our evals, our leaderboards and other public leaderboards
• Publish and open-source. Write up the problem, the eval, the data and the results, and release the models. We want this work to be cited and built on, not just shipped