Staff Machine Learning Engineer

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

What the job involves

• 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
• 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

Benefits

• Extensive learning opportunities, through our dedicated team, GreenHouse
• Flexible share incentives letting you choose how you share in our success
• Global parental leave, six months off - fully paid - for all new parents
• All The Feels, our employee assistance program and self-care hub
• Flexible public holidays, swap days off according to your values and beliefs