Why This Job is Featured on The SaaS Jobs
This Engineering Manager role sits at a SaaS scale where machine learning is no longer an R and D side project but a production capability. The remit spans the full lifecycle from experimentation systems and training pipelines through to deployment, which reflects a mature platform environment with real user impact and meaningful operational constraints.
For a SaaS career path, the standout value is the combination of people leadership and platform thinking in an ML context. Owning an engineering roadmap while partnering across research, product, and platform teams builds the kind of cross-functional operating muscle that translates across many SaaS organizations adopting AI features. The emphasis on reproducibility, shared tooling, and moving prototypes into reliable systems also maps closely to how SaaS companies de-risk innovation and turn it into maintainable product surface area.
This role tends to suit managers who enjoy setting technical direction without losing touch with engineering fundamentals, particularly in environments where research and production have to coexist. It is a strong match for leaders who like clarifying ambiguous problem spaces, aligning stakeholders around practical milestones, and building team practices that support both iteration and dependable delivery.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
We are looking for an Engineering Manager to lead the Research Engineering team in our Artist-First AI Music Lab. In this role, you will be a key driver of technical excellence, infrastructure, and deployment of state-of-the-art machine learning models.
You will manage a team of research engineers working at the intersection of deep learning research and large-scale software engineering. You will own the engineering roadmap, ensuring our research codebases support rapid experimentation, our training pipelines are efficient and reproducible, and our breakthroughs successfully transition from experimental prototypes into production features used by hundreds of millions of listeners.Our lab pioneers and advances state-of-the-art generative technologies for music to create new experiences for fans and artists. We build entirely new ways of listening that center and celebrate artists and creatives.
Our work is guided by four core principles:
- Partnerships with record labels, distributors, and music publishers: we develop new products through upfront collaboration
- Choice in participation: artists and rightsholders decide if and how they engage with generative AI tools
- Fair compensation and new revenue: we create new revenue streams while ensuring proper credit and compensation
- Artist-fan connection: our tools are designed to support creativity and deepen the relationship between artists and fans
For more information, see this press release:
https://newsroom.spotify.com/2025-10-16/artist-first-ai-music-spotify-collaboration/\n
What You'll Do
- Lead and support a team of research engineers and machine learning engineers, helping them grow and do their best work
- Define and deliver the engineering roadmap, balancing fast experimentation with production readiness
- Build and scale machine learning infrastructure, including training pipelines, experimentation systems, and shared tooling
- Partner with research scientists, product managers, and platform teams to bring ideas from research into user-facing features
- Improve engineering practices in a research environment, including testing, reproducibility, and deployment workflows
- Support the transition of research prototypes into reliable, scalable production systems
- Contribute to strategic planning and align engineering work with broader company priorities
Who You Are
- You have experience leading or managing engineering teams, ideally in machine learning or research-focused environments
- You are experienced with machine learning systems and frameworks such as PyTorch, TensorFlow, or JAX
- You understand distributed systems and have worked with large-scale training or compute environments
- You communicate clearly and collaborate effectively across research and engineering disciplines
- You have partnered with product and cross-functional teams to deliver meaningful outcomes
- You have delivered complex technical projects and can balance experimentation with reliability
- You care about building inclusive teams and supporting engineers at different stages of their careers
- You have an interest in music technology, audio, or generative AI
Where You'll Be
- We offer you the flexibility to work where you work best! For this role, you can be within the North Americas region as long as we have a work location.
- This team operates within the Eastern Standard time zone for collaboration.
- This team collaborates across regions, with core working hours typically overlapping between CET 3pm–6pm and EST 9am–12pm.
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The United States base range for this position is $184,050 – $262,928 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.
