研究工程师, Post-Training

Deepgram 招聘后训练研究工程师，加入构建大规模客户问题解决引擎的团队：定位语音 AI 模型的不足，设计评估、准备数据并微调模型，快速将改进投入生产。 岗位为全职，工作地点为美国远程或旧金山、纽约市。

• 找出语音 AI 模型未达标的场景，设定可衡量的改进目标，并持续跟踪生产中的改善。
• 设计评估方案，说明模型是否变得更好以及为什么更好。
• 整理和生成训练数据，并微调模型。
• 快速搭建可用系统并投入生产，在数周内将修复交付给所有客户。
• 将模型扩展到新的语言和地区，并改进 TTS 对姓名、术语和数字的发音。
• 将说话人的声音从背景噪声和串音中分离出来。
• 让客户提前使用可操控声音、克隆声音等新语音能力，并用客户反馈指导研究方法。
• 发布面向 Voice AI 用例的新基准。

• 具备训练、微调和评估深度学习模型的深入经验。
• 具备扎实的 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，并在过程中学习所需知识。
• 能判断哪些问题重要，以及结果何时适合交付给客户。
• 能将模糊的客户问题转化为清晰指标，并愿意使用微调、新数据或外部模型等有效方法解决。
• 积极使用并试验先进 AI 工具，能快速采用新模型和新工作方式，适应快速变化、非高度指令化的工作节奏。

• 全职岗位。
• 工作地点选项为美国远程、旧金山或纽约市；其中远程岗位标注为 USA
• Remote，不等同于全球任何地点均可申请。
• 招聘信息未进一步说明居住地、工作许可、时区、语言或出差要求，申请前应按原始招聘信息核实。
• 不要求特定学位；可通过过往项目、已上线系统或开源工作展示解决难题的能力。

• 有语音转文字（STT）、文字转语音（TTS）或语音智能体经验。
• 有分布式训练经验。
• 发表过论文、贡献过开源项目或参与过公开基准。

• 年薪 $178K - $268K USD / year。

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.

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 e 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.

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…