出海雷达

Internship - Applied Research Scientist

开发工程限定地区(需当地身份)
公司Smule,Inc.
薪资未公开
工作地点United States
地域资格限定地区(需当地身份)
时区要求日间重叠约 9 小时,基本正常作息
用工类型Intern
发布时间今天
数据来源Himalayas
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注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。
关于本页中文:职位描述由本机离线模型翻译,属机器翻译,供快速判断用;正式沟通与投递请以英文原文为准。官方翻译通道恢复后会自动重译升级。

斯穆尔自2008年以来一直在使命,通过音乐汇集世界。音乐不仅仅是听力...它就创造,分享,发现,参与和与人们联系而言。随着每月数百万活跃用户每天创建超过2000万首歌,Smule 正在通过制作音乐的快乐来连接世界各地的人们,并将音乐景观从被动倾听到协作创意表达和积极参与的东西转变为一体。关于角色:我们寻找一个研究科学家用于 Smule 应用研究团队,谁勃发展在尖端 ML 研究和现实世界的产品影响交叉点。你将从研究界面的想法中获得,或者创建自己的想法,并将其发展成改善 Smule 产品,管道和用户体验的实际解决方案。理想的候选人结合了深度研究与强大的工程本能,对可测量的结果的偏见以及人们如何制作音乐的真实好奇心。我们强烈鼓励非传统 ML 背景的候选人在申请。如果你进入应用机器学习的道路是通过音频工程,音乐生产,信号处理,数据科学或其他领域,我们希望听到你的话。· 开发和调整最先进的 ML 技术,以解决在音频处理,内容理解,推和生成音乐等领域的具体产品挑战,从而提高质量,延迟或用户体验。· 在生产部署前设计和运行严格的离线和在线实验 (A/B 测试,废除研究)来验证模型改进。· 与产品经理,设计师和工程师密切合作,将用户需求转化为精确的研究问题。·构建原型模型和概念证明系统,证明可行的并通知生产架构决策。· 通过技术讨论和文档,在相关场所发表应用研究成果并促进内部知识共享。· 监测部署的漂移,公平性和性能模型,实施持续改进循环。我们正在寻找什么:· 计算机科学 (BS,MS 或博士学位),软件工程,电气工程或相关技术学科,或者目前正在追求其中一个。· 证明从纸质到生产的研究想法的能力,以 ex

查看英文原文

Smule has been on a mission to bring the world together through music since 2008. Music is much more than listening… it's about creating, sharing, discovering, participating, and connecting with people. With dozens of millions of monthly active users creating over 20 million songs every day, Smule is connecting people all over the world through the joy of making music and transforming the music landscape from one of passive listening to collaborative creative expression and active engagement.
About the Role:
We are seeking a Research Scientist for Smule's Applied Research team who thrives at the intersection of cutting-edge ML research and real-world product impact. You will take ideas from the research frontier, or originate your own, and develop them into practical solutions that improve Smule's products, pipelines, and user experience for a community of millions. The ideal candidate combines research depth with strong engineering instincts, a bias toward measurable outcomes, and genuine curiosity about how people make music.
We strongly encourage candidates with non-traditional ML backgrounds to apply. If your path into applied machine learning came through audio engineering, music production, signal processing, data science, or another field, we want to hear from you.
What You'll Be Doing:

  • Develop and adapt state-of-the-art ML techniques to solve concrete product challenges in areas such as audio processing, content understanding, recommendation, and generative music, delivering measurable improvements in quality, latency, or user experience.
  • Design and run rigorous offline and online experiments (A/B tests, ablation studies) to validate model improvements before production deployment.
  • Collaborate closely with product managers, designers, and engineers to translate user needs into well-scoped research problems.
  • Build prototype models and proof-of-concept systems that demonstrate feasibility and inform production architecture decisions.
  • Publish applied research findings at relevant venues and contribute to internal knowledge-sharing through tech talks and documentation.
  • Monitor deployed models for drift, fairness, and performance, implementing continuous improvement loops.

What We're Looking For:

  • Degree (B.S., M.S., or Ph.D.) in Computer Science, Software Engineering, Electrical Engineering, or a related technical discipline, or currently pursuing one.
  • Demonstrated ability to take research ideas from paper to production, with experience shipping ML-powered features or systems.
  • Strong skills in experiment design, statistical analysis, and iterative model development.
  • Proficiency in Python, PyTorch or TensorFlow, and standard ML infrastructure (data pipelines, model serving, monitoring).
  • Effective communicator who can translate between research concepts and product requirements.
  • Track record of identifying high-impact problems and delivering solutions with measurable outcomes.

Bonus Points For:

  • Experience with audio, speech, music, or multimedia ML applications.
  • Familiarity with on-device or edge deployment constraints (model compression, quantization, latency optimization).
  • Published work at conferences or journals, such as KDD, RecSys, EMNLP, Interspeech, ISMIR, or similar.

Smule is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, gender identity or expression, sexual orientation, national origin, ancestry, age, disability, medical condition, genetic information, marital status, military or veteran status, or any other protected characteristic under federal, state, or local law.
We are committed to creating an inclusive environment for all employees and applicants. If you require a reasonable accommodation during the application or interview process, please let us know.
Originally posted on Himalayas

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