Research 资深, Applied Voice AI

PromptCube

New York (NY)

Remote

USD 178,000 - 268,000

Full time

2 days ago
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美国远程工作

Job summary

Deepgram 正在美国多地招聘应用语音 AI 研究员,负责定位模型在客户场景中的不足,设计评测、整理与生成数据、微调模型,并快速将修复投入生产。该岗位为全职,工作地点为美国远程或旧金山、纽约市。

职位要求具备训练、微调和评估深度学习模型的深入经验,精通 Python 与 PyTorch,且有将机器学习系统落地到生产的记录。候选人应具备端到端负责问题、快速学习和在 AI-first 工作方式下应用先进工具的能力。

Qualifications

  • 熟练训练、微调和评估深度学习模型。
  • 具备较强的 Python 和 PyTorch 技能。
  • 有将 ML 系统落地到生产环境的经验。
  • 具备端到端负责问题的能力,能自主学习。
  • 能判断哪些问题重要以及何时交付给客户。
  • 不限定特定学位,需通过项目/开源工作证明能力。
  • 愿意在 AI-first 的工作方式下快速采用新模型与方法。

Responsibilities

  • 定位客户场景中的模型短板并转化为评估指标。
  • 设计评估以判断模型改进效果及原因。
  • 整理并生成数据,微调模型,必要时引入新数据或外部模型。
  • 快速搭建可用系统并投入生产,使改进在数周内被使用并持续追踪。
  • 将模型扩展到新语言和地区。
  • 改进文本转语音对姓名、术语和数字的发音。
  • 从背景噪声中分离发言人声音。
  • 向客户展示可控语音等新能力并据反馈调整研究方法。
  • 发布面向语音 AI 用例的新基准。

Skills

深度学习训练
微调评估
Python
PyTorch
上线生产

Tools

分布式训练

Job description

岗位概况

Deepgram 招聘应用语音 AI 研究员,负责定位语音模型在客户场景中的不足,设计评测、整理与生成数据、微调模型,并快速把修复投入生产;该岗位为全职,工作地点为美国远程或旧金山、纽约市。

工作职责
  • 定位模型在客户语音场景中的短板,把模糊的客户问题转化为清晰指标,并设定改进目标。
  • 设计评测,判断模型是否变得更好,以及改进的原因。
  • 整理和生成数据并微调模型;必要时采用新数据、外部模型等可行手段解决问题。
  • 快速搭建可用系统并投入生产,让客户在数周内用上改进,并持续负责到指标取得可衡量的提升。
  • 将模型扩展到新的语言和地区。
  • 改进文本转语音对姓名、术语和数字的发音。
  • 从背景噪声和串话中分离说话人的声音。
  • 向客户提前开放可操控语音、克隆语音等新能力,用客户反馈指导研究方法,并发布面向语音 AI 用例的新基准。
任职要求
  • 具备训练、微调和评估深度学习模型的深入经验。
  • 具备较强的 Python 和 PyTorch 技能。
  • 有将机器学习系统交付到生产的记录。
  • 习惯端到端负责问题,并在需要时主动学习。
  • 能判断哪些问题重要,以及结果何时适合交付给客户。
  • 不限特定学位;需通过过往项目、已交付系统或开源工作展示解决过的难题。
  • 按公司 AI-first 的工作方式,主动使用并试验先进 AI 工具,将 AI 融入日常工作,并能快速采用新模型和新方法。
申请条件与限制
  • 全职岗位。
  • 工作地点可选:美国远程;加利福尼亚州旧金山;纽约州纽约市。
  • 远程岗位不代表全球均可申请,申请者需对照原招聘信息确认自身是否符合当地申请资格。
  • 原文未说明具体的居住地、工作许可、时区、语言、到岗频率或出差要求。
加分项
  • 有语音转文字(STT)、文本转语音(TTS)或语音智能体经验。
  • 有分布式训练经验。
  • 发表过论文、有开源贡献或公开基准。
薪酬与福利
  • 年薪 178K–268K 美元(USD),按年计。

国际远程岗位,招聘地区:USA

  • Remote; San Francisco, CA; New York City, NY。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): USA

  • Remote; San Francisco, CA; New York City, NY. 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 building the engine that solves customer challenges at scale. When customers hit a limit in our voice AI, you'll measure it, fix it, and ship the fix to every customer in weeks.

Example projects:

  • Expanding our models to new languages and regions
  • Improving how text-to-speech pronounces names, terms, and numbers
  • Isolating a speaker's voice from background noise and crosstalk
  • Giving customers early access to new voice capabilities, like steerable and cloned voices, and using their feedback to guide the research methodology
  • Releasing new benchmarks for Voice AI use-cases
The Role

You will thrive in this role if you enjoy:

  • Turning vague customer problems into clear metrics
  • Using whatever works to fix them, including fine-tuning, new data, and external models
  • Shipping work that customers use within weeks
The Challenge

We are seeking researchers who:

  • Own a customer problem until it measurably improves in production
  • Find the fastest path to a fix, even if it's an approach no one has tried
  • Can tell when a result is ready for customers

If these expectations energize you, you might be the person we need. This role takes focus on the customer's problem, creativity in approach, and a strong drive to ship.

What You'll Do
  • Find where our models fall short and set targets for improvement
  • Design evaluations that show whether a model is better and why
  • Curate and generate data and fine-tune models
  • Build working systems quickly and ship them to production

We don't require a specific degree. Show us hard problems you've solved in past projects, shipped systems, or open source work.

You May Be a Good Fit If You Have
  • Deep experience training, fine-tuning, and evaluating deep learning models
  • Strong Python and PyTorch skills
  • A track record of shipping ML to production
  • A habit of owning problems end to end and learning what you need along the way
  • Good judgment about which problems matter and when a result is ready to ship
Strong Candidates May Have
  • Experience with speech-to-text, text-to-speech, or voice agents
  • Experience with distributed training
  • Published papers, open source contributions, or public benchmarks

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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