机器学习研究员（语音/音频）
Machine Learning Researcher (Speech/Audio)
Brahma 是一家开创性的企业人工智能公司，开发 Astra 系列产品，这些是为帮助企业与创作者大规模创新而打造的原生 AI 产品。Brahma 让团队能够突破创意瓶颈，加速叙事创作，并高效地交付出色的内容。作为 DNEG 集团的一部分，Brahma 汇聚了好莱坞领先的创意技术专家、AI 和生成式 AI 的创新者，以及 AI 内容伦理创作的思想领袖。
我们正在寻找一名机器学习研究员加入团队，参与下一代语音合成模型的开发。你将研究并构建深度学习系统，从文本或音频提示中生成富有表现力、自然的声音，并与跨职能团队合作，将你的工作集成到可生产使用的流程中。
主要职责
- 研究和开发最先进的语音合成模型（例如 TTS、语音克隆、语音到语音）。
- 使用 PyTorch 和 HuggingFace 等框架构建和优化模型。
- 设计用于可扩展语音模型训练的训练流程和数据集。
- 探索情感表达、多语言合成和说话人适应等技术。
- 与产品和创意团队紧密合作，确保模型满足质量和生产约束。
- 关注语音合成及相关领域的学术和工业趋势。
必备条件
- 具有机器学习和深度学习背景，重点在语音/音频领域。
- 有 TTS、语音克隆或相关语音合成任务的实际经验。
- 精通 Python 和 PyTorch；有 torchaudio、ESPnet 或类似库的经验。
- 有大规模训练模型和处理大型音频数据集的经验。
- 熟悉声码器和基于 Transformer 的架构。
- 强大的问题解决能力，能够在以远程为主的工作环境中独立工作。
加分项
- 计算机科学/机器学习博士学位，且在顶级会议或期刊上有发表论文。
- 对开源语音研究有贡献或参与过相关基准测试。
- 熟悉唇形同步、音频驱动动画或富有表现力的语音控制等相邻领域。
- 有语音数据集或专有流程的经验。
最初发布于 Himalayas
查看英文原文
Brahma is a pioneering enterprise AI company developing Astras, AI-native products built to help enterprises and creators innovate at scale. Brahma enables teams to break creative bottlenecks, accelerate storytelling, and deliver standout content with speed and efficiency. Part of the DNEG Group, Brahma brings together Hollywood’s leading creative technologists, innovators in AI and Generative AI, and thought leaders in the ethical creation of AI content.
We are looking for a Machine Learning Researcher for Audio to join our team and help develop next-generation voice synthesis models. You'll research and build deep learning systems that can generate expressive, natural-sounding speech from text or audio prompts, and collaborate with cross-functional teams to integrate your work into production-ready pipelines.
Key Responsibilities
- Research and develop state-of-the-art voice synthesis models (e.g., TTS, voice cloning, speech-to-speech).
- Build and fine-tune models using frameworks like PyTorch and HuggingFace.
- Design training pipelines and datasets for scalable voice model training.
- Explore techniques for emotional expressiveness, multilingual synthesis, and speaker adaptation.
- Work closely with product and creative teams to ensure models meet quality and production constraints.
- Stay on top of academic and industrial trends in speech synthesis and related fields.
Must Haves
- Strong background in machine learning and deep learning, with focus on speech/audio.
- Hands-on experience with TTS, voice cloning, or related voice synthesis tasks.
- Proficiency with Python and PyTorch; experience with libraries like torchaudio, ESPnet, or similar.
- Experience training models at scale and working with large audio datasets.
- Familiarity with vocoders and transformer-based architectures.
- Strong problem-solving skills, ability to work autonomously in a remote-first environment.
Nice to Have
- PhD degree in Computer Science/ Machine Learning and publications in top venues.
- Contributions to open-source speech research or participation in relevant benchmarks.
- Familiarity with adjacent areas like lip-syncing, audio-driven animation, or expressive speech control.
- Experience with voice datasets or proprietary pipelines.
Originally posted on Himalayas