研究主管，语音合成
Director of Research, Text to Speech
## **公司简介**
Deepgram 是支撑新兴数千亿美元语音 AI 经济的领先平台，提供实时 API 服务，包括语音转文本（STT）、文本转语音（TTS），以及大规模构建生产级语音代理。超过 20 万名开发者和 1300 多家组织正在构建“由 Deepgram 提供支持”的语音产品，包括 Twilio、Cloudflare、Sierra、Decagon、Vapi、Daily、Cresta、Granola 和 Jack in the Box。Deepgram 的语音原生基础模型可通过云 API 或自托管及本地部署软件访问，具有无与伦比的准确性、低延迟和成本效率。由领先的全球投资者和战略合作伙伴主导的最新 C 轮融资支持，Deepgram 已处理超过 5 万年的音频，并转录了超过 1 万亿个单词。世界上没有哪家公司比 Deepgram 更了解语音。
## **公司运作节奏**
在 Deepgram，我们期望具备 AI 首先的思维模式——AI 的使用和熟悉程度不是可选的，而是我们运营、创新和衡量绩效的核心。
每位在 Deepgram 工作的团队成员都应积极使用和试验先进的 AI 工具，甚至将它们融入日常工作中。我们衡量 AI 应用的效果以实现成果，持续且富有创意地使用最新 AI 能力是这里成功的关键。候选人应能够快速采用新模型和新模式，将 AI 整合到自己的工作流程中，并不断推动这些技术的边界。
此外，我们以 AI 的速度前进。变化迅速，你每天的工作也会随之快速变化。如果你对实验、适应、临场反应和不断学习不感兴趣，或者你寻求的是高度规范化的传统朝九晚五工作，那么这可能不是适合你的职位。
### 机会介绍
我们正在寻找一位研究总监，全面负责我们的文本转语音（TTS）项目——从研究策略、技术决策到最终发布的模型。这是一个需要亲力亲为的领导角色：你设定方向并深入细节，塑造架构、实验、训练策略和评估。你还将建立一个团队和运营模式，让优秀的研究人员在不降低标准的前提下快速行动。
使命范围广泛：推进语音生成的技术前沿，并将这些进展转化为生产中的模型。
### 你将负责
- 全面负责 TTS 研究和模型研发
- 制定研究战略，确定技术方向
- 设计和优化模型架构，推动实验和训练策略
- 建立高效的评估体系，确保模型质量
- 搭建高效的研究团队和运营机制，提升整体研发效率
- 与工程、产品和业务团队紧密合作，推动研究成果落地
- 跟踪行业动态和技术趋势，保持技术领先性
查看英文原文
## **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_](http://deepgram.com) _email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com._