Head of ML

Apply on YC · Original job listing

• Role: Engineering / Machine learning
• Experience: 3+ years
• Visa: US citizen/visa only
• Skills: Machine Learning, Speech Recognition

We are looking for the person who will own the central machine learning problem at Subvocal: turning weak, noisy, highly variable physiological signals into continuous language.

We have already built prototypes that decode subvocal speech at more than 200 words per minute. The much harder problem now is generalization. A model that works on one person, in one session, with one device placement is not a product. It needs to work when the same person returns the next day, when the hardware moves slightly, and eventually when a completely new person puts it on and gives us only a few minutes of calibration data.

You will lead that effort end to end. You will work directly with the founders and our sensing and hardware leads to decide what data we collect, how we represent the signal, which model families we pursue, and how we evaluate whether we are actually making progress.

Some of the problems you will work on include:

• Learning general representations from large amounts of unlabeled and weakly labeled physiological time-series data.
• Building continuous sequence models using approaches such as Conformers, Mamba-style architectures, CTC, transducers, and pretrained speech or language models.
• Separating speech-related information from anatomy, placement, session, device, and environmental variation.
• Adapting a large cross-user model to a new person from roughly 15 minutes of calibration data.
• Designing honest user-held-out, session-held-out, and device-held-out evaluations.
• Scaling training across thousands of hours and thousands of people.