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Deepgram

Director of Research, Text to Speech

Deepgram is hiring a Director of Research, Text to Speech for a remote role open to applicants in United States. It pays $213k-$328k a year and Level rates it ; you can apply on Deepgram.

Level's read on this job

  • Level rates this role Builds AI ●●●●: the job is building AI systems.
  • This is listed as a remote role.
  • The posting mentions Sierra, Decagon and Python among its tools and skills.
  • Level classes it as a lead role.
  • Deepgram has 80 other open roles on Level.

AI in this role

Own the text-to-speech research strategy, technical bets, and model development as a hands-on leader at Deepgram.

sierradecagonpythonpytorch
speechai-researchmachine-learningdeep-learningspeech-recognitiontext-to-speechresearch
Company Overview

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 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s 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 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram.

Company Operating Rhythm

At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re 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 you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5.

The Opportunity

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.

What You'll Do

  • 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.

  • Get energy from deciding which bets are worth making when the answer isn't obvious and the experiments are expensive.

You Must Have

  • 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 aren't 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. You've rebuilt how you and your team operate around it, and you have a specific, earned view of what it still can't do in speech research.

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

It'd Be Great If You Had

  • 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.

Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.

How we rate this

Director of Research, Text to Speech at Deepgram rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

SpeechAI ResearchMachine learningDeep learningSpeech RecognitionText To SpeechResearchSierra

Questions you could be asked

  1. What have you built with speech recognition or text-to-speech, and where did it break?
  2. Tell me about a research question you investigated. What did you find?
  3. Tell me about a project where machine learning was part of your work. What did you do?
  4. Tell me about a project where deep learning was part of your work. What did you do?
  5. Tell me about a project where speech recognition was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Speech, AI Research, Machine learning, Deep learning, and Speech Recognition. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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