Deepgram Director of Text-to-Speech Synthesis Research at Deepgram owning the research strategy and model development for TTS. Leads technical direction, experiments, and team building to advance speech generation quality.
Responsibilities
We're looking for a Director of Research to own our Text-to-Speech program end to end — the research strategy, the technical bets, and the models that ship. This is a hands-on leadership role: you set direction and stay in the details, shaping architectures, experiments, training strategy, and evaluation. You'll also build the team and operating model that let exceptional researchers move fast without lowering the bar.
The mandate is broad: advance the state of the art in speech generation, and turn those advances into models in production.
Own the TTS research and model roadmap — decide which technical directions can materially move speech-generation quality, including the expensive and non-obvious ones, and recognize when an approach should change or die.
Drive advances across neural audio modeling, prosody and expressiveness, controllability, multilingual speech, voice identity and consistency, data and training strategy, post-training, and inference performance — and make sure they land as measurable production gains.
Stay deeply technical: review research, challenge assumptions, design experiments, diagnose model failures, and take on the highest-leverage problems yourself.
Build evaluation and benchmarking that explains why models improve, not just whether they did — automated metrics alongside human perceptual assessment.
Lead a mix of individual contributors and tech lead managers. Hire and develop both, hold an exceptionally high technical bar, grow senior researchers into technical leaders, and set direction across sub-teams while pushing decisions down to the people closest to the work.
Partner with engineering and product leadership on ship-readiness, and represent Deepgram's TTS research internally and externally.
You'll Love This Role If You
Want to own a frontier-model program end to end rather than optimize one slice of someone else's agenda.
Care about the breakthrough and the ship in equal measure.
Still love training runs, failed evals, and architecture arguments, even as most of your impact now comes through the people you lead.
