Director, Text-to-Speech Synthesis Research

Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy providing real-time APIs for speech-to-text (STT) text-to-speech (TTS) and building production-grade voice agents at scale. More than 200000 developers and 1300 organizations build voice offerings that are Powered by Deepgram including Twilio Cloudflare Sierra Decagon Vapi Daily Cresta Granola and Jack in the Box. Deepgrams voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software with unmatched accuracy low latency and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners Deepgram has processed over 50000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.

At Deepgram we expect an AI-first mindsetAI use and comfort arent optional theyre core to how we operate innovate and measure performance.

Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools and even build your own into your everyday work. We measure how effectively AI is applied to deliver results and consistent creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly integrating AI into their workflows and continuously pushing the boundaries of what these technologies can do.

Additionally we move at the pace of AI. Change is rapid and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if youre not excited to experiment adapt think on your feet and learn constantly or if youre seeking something highly prescriptive with a traditional 9-to-5.

Were 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. Youll 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 Deepgrams TTS research internally and externally.
  

• Want to own a frontier-model program end to end rather than optimize one slice of someone elses 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.

• Get energy from deciding which bets are worth making when the answer isnt obvious and the experiments are expensive.
  

• Deep expertise in modern TTS speech generation or audio generative modeling with a track record of personally training and improving large-scale neural models.

• Command of the modern speech-generation stack and the open problems behind naturalness expressiveness controllability robustness voice consistency and inference cost.

• A history of setting research direction under genuine uncertainty: prioritizing experiments allocating compute and researcher time and killing approaches that arent working.

• Experience leading researchers and research engineers through other technical leaders developing tech lead managers or equivalent setting direction across sub-teams while staying technically influential yourself.

• AI as your default mode of work not an occasional tool. Youve rebuilt how you and your team operate around it and you have a specific earned view of what it still cant do in speech research.

• The ability to make complex technical tradeoffs legible to product engineering and executive audiences.
  

• TTS or generative-audio models deployed at meaningful production scale.

• Built or substantially scaled a high-performing AI research organization.

• Sophisticated evaluation systems for generative speech; expressive or multilingual generation voice cloning and adaptation or controllable generation.

• Recognized external contributions publications open source patents invited talks in speech synthesis neural audio codecs speech language models or multimodal models.

• Experience in fast-moving startup or research environments that routinely take models from idea to production.

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Required Experience:

Director