资深机器学习工程师 - 音乐使命
Staff Machine Learning Engineer - Music Mission
音乐使命团队负责Spotify面向音乐创作者的端到端服务以及他们为粉丝打造的体验。该团队致力于构建工具和服务，以实现大规模的创作、推广、表达和变现。
DISCO产品领域专注于构建帮助艺术家触达更多粉丝的推广工具。我们的产品通过Spotify for Artists服务于大量艺术家，并且我们正在利用Discovery Mode的势头，帮助艺术家及其团队在最关键的时候找到新听众。作为资深机器学习工程师，你将参与塑造这一高影响力领域的机器学习技术战略，与工程、产品、数据科学、研究和设计团队合作，打造帮助艺术家扩大受众的工具，同时支持Spotify的核心业务。
该职位在美国的薪资范围为227,495.00至324,993美元，加上股权。该职位提供的福利包括健康保险、六个月带薪育儿假、401(k)退休计划、每月餐饮补贴、23天带薪假期、带薪灵活假日和带薪病假。此薪资范围可能会在未来进行调整。
Spotify是平等机会雇主。无论你来自哪里、长什么样，或者耳机里播放的是什么，你都可以在Spotify找到属于自己的位置。我们的平台属于每个人，我们的工作场所也是如此。我们业务中代表和放大越多的声音，我们就能更加繁荣发展、做出贡献并保持前瞻性！所以，请带来你的个人经历、观点和背景。正是在我们的差异中，我们将找到推动世界聆听方式不断革新的力量！
在Spotify，我们热衷于包容性，并确保整个招聘过程对每个人都是可访问的。我们在面试过程中有方式可以请求合理的便利措施，并协助满足你的需求。如果你在申请或面试过程的任何阶段需要便利措施，请告诉我们——我们会尽最大努力支持你。
Spotify在2008年推出后彻底改变了音乐聆听方式。我们的使命是通过给予一百万名创意艺术家靠艺术生活的机会，以及数十亿粉丝享受并热爱这些创作者的机会，来释放人类创造力的潜力。我们所做的每一件事都源于我们对音乐和播客的热爱。如今，我们是全球最受欢迎的音频平台。
查看英文原文
The Music Mission team owns Spotify’s end to end proposition for music creators and the experiences they create for fans. The team is dedicated to building tools and services to enable creation, promotion, expression, and monetization at scale.
The DISCO Product Area is focused on building promotional tools that help artists reach more fans. Our products serve artists at scale through Spotify for Artists, and we’re building on the momentum of Discovery Mode to help artists and their teams find new listeners when it matters most. As a Staff Machine Learning Engineer, you’ll help shape the Machine Learning technical strategy for this high-impact area, partnering across engineering, product, data science, research, and design to create tools that help artists grow their audiences while supporting Spotify’s core business.
The United States base range for this position is $227,495.00 - $324,993 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future
Spotify is an equal opportunity employer. You are welcome at Spotify for who you are, no matter where you come from, what you look like, or what’s playing in your headphones. Our platform is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all thrive, contribute, and be forward-thinking! So bring us your personal experience, your perspectives, and your background. It’s in our differences that we will find the power to keep revolutionizing the way the world listens.
At Spotify, we are passionate about inclusivity and making sure our entire recruitment process is accessible to everyone. We have ways to request reasonable accommodations during the interview process and help assist in what you need. If you need accommodations at any stage of the application or interview process, please let us know - we’re here to support you in any way we can.
Spotify transformed music listening forever when we launched in 2008. Our mission is to unlock the potential of human creativity by giving a million creative artists the opportunity to live off their art and billions of fans the chance to enjoy and be passionate about these creators. Everything we do is driven by our love for music and podcasting. Today, we are the world’s most popular audio streaming subscription service.
What You'll Do
- Help define and drive the Machine Learning engineering strategy for Discovery Mode and related royalty programs, translating product goals into scalable technical solutions.
- Design, build, evaluate, ship, and refine production Machine Learning systems through hands-on development.
- Provide technical leadership across complex ML initiatives, helping teams make thoughtful architectural and engineering decisions while balancing near- and long-term priorities.
- Collaborate with user research, design, data science, product management, and engineering to build new product capabilities that strengthen connections between artists and fans.
- Prototype new approaches and turn successful ideas into reliable, scalable solutions for Spotify for Artists customers.
- Drive experimentation, optimization, testing, and tooling that improve the quality, reliability, and effectiveness of our Machine Learning systems.
- Partner with engineers and Machine Learning practitioners across Spotify, including Music Tech Research and Personalization, to explore and develop new approaches to music promotion.
- Help grow the technical capabilities of the broader engineering community through mentorship, knowledge sharing, and strong engineering practices.
Who You Are
- You have deep experience with Machine Learning and a strong understanding of Machine Learning algorithms, modeling approaches, evaluation, and experimentation.
- You have hands-on experience designing and implementing production Machine Learning systems at scale using languages such as Python, Java, Scala, or similar.
- You can set technical direction for complex ML problems while remaining close to implementation and delivery.
- You care about reliable software, data-informed development, disciplined experimentation, and building systems that perform effectively at scale.
- You enjoy leading technically complex projects from idea through production and working closely with teammates and partners to deliver meaningful outcomes.
- You are comfortable navigating ambiguity, evaluating trade-offs, and creating clarity on high-impact initiatives.
- You communicate technical decisions and risks clearly and can build alignment with senior technical leaders and cross-functional partners.
- You care about creating products that better serve artists and their teams, and you take a collaborative, team-first approach to helping others do their best work.
Where You'll Be
- We offer you the flexibility to work where you work best! For this role, you can be within the North America region as long as we have a work location.
- This team operates within the Eastern time zone for collaboration.