Research Scientist - Generative Audio

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We are seeking Research Scientists (across all levels of seniority) to join our Artist-First AI Music Lab. Our team pioneers and advances state-of-the-art generative technologies for music that create breakthrough experiences for fans and artists. We invent entirely new listening experiences that center and celebrate artists and creatives. All of our products will put artists and songwriters first, through these four principles: Partnerships with record labels, distributors, and music publishers : We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later. Choice in participation : We recognize there’s a wide range of views on the use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music. Fair compensation and new revenue : We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for the use of their work and transparently credited for their contributions. Artist-fan connection : AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will leverage our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections. Learn more in our press release: What You'll Do Conduct groundbreaking research in generative audio using diffusion or flow matching models, with a focus on one or more of the following areas: Vocal Synthesis — Research in vocal and speech synthesis, along with related areas such as ML-based audio processing and signal processing. Post-Training — Research in post-training techniques for music generation, including preference alignment methods (such as DPO, RLHF, or KTO), reward model design and training, and reinforcement learning to improve output quality, controllability, and human preference adherence. Editing — Research in iterative music generation and audio editing, including capabilities such as stem replacement, instrumentation change, mood changes (while preserving content), tempo changes, and structure changes. You will also: Run large-scale experiments with access to Spotify 's extensive infrastructure and an audience of more than 700 million monthly active users. Create practical applications that harness generative technologies and push the boundaries of what's possible in listening experiences. Collaborate as part of a cross-functional team—working closely with scientists, engineers, product managers, designers, user researchers, and analysts—to craft innovative solutions to complex challenges. Have a direct impact on Spotify 's products, tools, and services, working on projects that influence the entire organization. Engage with the broader research community by publishing your findings, delivering talks, and attending top conferences. Who You Are You have a Ph.D. in Computer Science, Mathematics, Engineering, or a related field. Previous industry experience is helpful. You have experience in one or more of the following fields: generative modeling, machine learning, music information retrieval, speech processing, audio processing, signal processing, probabilistic modeling, computer vision, or related areas. You have deep expertise in at least one of the focus areas above—whether that's vocal/speech synthesis, post-training alignment techniques (e.g., PPO, GRPO, DPO), or audio-to-audio generation and text-guided music editing. You have publications at leading conferences such as ICASSP, ISMIR, INTERSPEECH, ICLR, AAAI, IJCAI, NeurIPS, ICML, CVPR, ECCV, ICCV, or related venues. You have strong coding skills in Python, PyTorch, and NumPy. You are a creative problem solver who is passionate about building outstanding products that add real value

我们正在招聘研究科学家（各级别资深程度均可）加入我们的“艺术家优先”AI音乐实验室。我们的团队开创并推进最先进的音乐生成技术，为粉丝和艺术家创造突破性体验。我们发明全新的聆听体验，以艺术家和创作者为中心并予以庆祝。我们的所有产品都将通过以下四项原则将艺术家和词曲作者放在首位：与唱片公司、分销商和音乐出版商建立合作伙伴关系：我们将通过预先协议为艺术家和粉丝开发新产品，而不是事后请求原谅。参与选择权：我们认识到，艺术界对生成式音乐工具的使用存在广泛不同的观点。因此，艺术家和权利持有人将选择是否以及如何参与，以确保AI工具的使用与音乐背后人们的价值观保持一致。公平报酬和新收入：我们将构建产品，为权利持有人、艺术家和词曲作者创造全新的收入来源，确保他们因作品的使用获得适当报酬，并因其贡献获得透明署名。艺术家与粉丝的连接：我们开发的AI工具不会取代人类艺术性。它们将为艺术家提供新的创作方式和与粉丝连接的方式。我们将利用我们作为每月已有超过7亿人前来听音乐的平台这一角色，确保生成式AI加深艺术家与粉丝之间的连接。在我们的新闻稿中了解更多：您将做什么 使用扩散模型或流匹配模型开展生成式音频方面的突破性研究，重点关注以下一个或多个领域：人声合成——研究人声和语音合成，以及相关领域，如基于机器学习的音频处理和信号处理。后训练——研究音乐生成的后训练技术，包括偏好对齐方法（如DPO、RLHF或KTO）、奖励模型设计与训练，以及强化学习，以提升输出质量、可控性和对人类偏好的遵循度。编辑——研究迭代式音乐生成和音频编辑，包括分轨替换、配器变更、情绪变更（同时保留内容）、速度变更和结构变更等能力。您还将：利用Spotify广泛的基础设施和超过7亿月活跃用户的受众，运行大规模实验。创建利用生成式技术的实际应用，并推动聆听体验的可能性边界。作为跨职能团队的一员协作——与科学家、工程师、产品经理、设计师、用户研究员和分析师密切合作——为复杂挑战打造创新解决方案。对Spotify的产品、工具和服务产生直接影响，参与影响整个组织的项目。通过与更广泛的研究社区互动，发表您的研究成果、进行演讲并参加顶级会议。您是谁 您拥有计算机科学、数学、工程或相关领域的博士学位。有行业经验者优先。您在以下一个或多个领域有经验：生成建模、机器学习、音乐信息检索、语音处理、音频处理、信号处理、概率建模、计算机视觉或相关领域。您在上述至少一个重点领域中拥有深厚专业知识——无论是人声/语音合成、后训练对齐技术（如PPO、GRPO、DPO），还是音频到音频生成和文本引导的音乐编辑。您在ICASSP、ISMIR、INTERSPEECH、ICLR、AAAI、IJCAI、NeurIPS、ICML、CVPR、ECCV、ICCV等顶级会议或相关场所有发表成果。您具备Python、PyTorch和NumPy的强编码能力。您是一位富有创造力的问题解决者，热衷于打造能够创造真正价值的卓越产品。

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