Director, Text-to-Speech Synthesis Research(语音合成研究总监)

岗位概况

Deepgram 招聘语音合成（TTS）研究总监，负责端到端掌管其文本转语音研究项目——包括研究战略、技术方向选择以及最终交付上线的模型。 这是一个亲力亲为的领导岗位：既要设定方向，也要深入细节，参与架构、实验、训练策略与评估的制定，同时搭建团队与运作模式。 工作地点为 London, UK，为全职雇主发布的远程岗位；远程并不代表全球均可申请。

工作职责

• 端到端掌管 TTS 研究与模型路线图，判断哪些技术方向能实质提升语音生成质量，包括昂贵且不显而易见的方向，并识别某条路线何时应当调整或终止。
• 推动神经音频建模、韵律与表现力、可控性、多语言语音、音色身份与一致性、数据与训练策略、后训练以及推理性能等方面的进展，并确保这些进展转化为可衡量的生产收益。
• 保持深度技术参与：审阅研究、质疑假设、设计实验、诊断模型失败，并亲自攻克最高杠杆的问题。
• 构建评估与基准体系，不仅说明模型是否改进，还要解释改进的原因——结合自动化指标与人类感知评估。
• 领导个人贡献者与技术负责人（tech lead manager）的混合团队：招聘并培养两类人才，维持极高的技术标准，将资深研究员培养为技术领导者，跨子团队设定方向，并把决策下放给最接近工作的人。
• 与工程和产品领导层就上线准备度协作，并在内部和外部代表 Deepgram 的 TTS 研究。

任职要求

• 在现代 TTS、语音生成或音频生成建模方面拥有深厚专长，并有亲自训练并改进大规模神经模型的过往记录。
• 精通现代语音生成技术栈，以及自然度、表现力、可控性、鲁棒性、音色一致性和推理成本等背后的开放问题。
• 有在真实不确定性下设定研究方向的经验：对实验排定优先级、分配算力与研究员时间，并终止无效路线。
• 有通过其他技术领导者（培养技术负责人或同等角色、跨子团队设定方向）领导研究员与研究工程师的经验，同时自身保持技术影响力。
• 将 AI 作为默认工作方式而非偶尔使用的工具：已围绕 AI 重建自己与团队的运作方式，并对它在语音研究中仍无法做到的事情有具体而切实的看法。
• 能够向产品、工程和高管受众清晰阐明复杂的技术权衡。

申请条件与限制

• 雇主发布的远程岗位，列明地点为 London, UK；远程并不意味着全球均可申请。
• employment_type 为全职。
• 需核对原招聘信息中的居住地、工作许可、时区、语言与出差要求。

加分项

• 有在具有实际意义的生产规模上部署 TTS 或生成式音频模型的经验。
• 曾建立或大幅扩展一支高绩效的 AI 研究组织。
• 构建过面向生成式语音的复杂评估体系；涉及表现力或多语言生成、声音克隆与适配，或可控生成。
• 在语音合成、神经音频编解码器、语音语言模型或多模态模型方面有公认的外部贡献——论文、开源、专利、受邀演讲。
• 有在快速发展的创业或研究环境中工作的经验，这类环境经常将模型从构想推进到生产。

国际远程岗位，招聘地区：London, UK。 请核对原招聘中的居住地、工作许可、时区、语言与出差要求；远程岗位不等于全球可申请。 以下保留招聘来源英文原文。

Employer-published remote role. Listed location(s): London, UK. Remote does not imply worldwide eligibility. Check the original listing for residency, work authorization, time zone, language and travel requirements.

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 cannot 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.

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