Engineering Manager - Machine Learning

Om jobbet

Join our global force of 500+ innovators, blending the latest in tech with the greatest in soundtracking, from our Stockholm HQ to offices in London, New York, Los Angeles, Berlin, Paris, Oslo, and Seoul. We're an industry leader with a startup mentality. We take what we do seriously, but we don't take ourselves too seriously. Creating and collaborating to transform the sound of streaming, content, and culture. Come join us, and let the world feel your work.

As an Engineering Manager, you will play a crucial role in the Powerful Controls team, focused on next-generation AI music adaptation and foley generation. This is a pivotal role where you will be accountable for people, delivery, process, and cross-team technical leadership, with a core mandate to ship and scale cutting-edge diffusion models for music. You will own the complete path from innovative research to low-latency, high-fidelity production, driving one of our most critical technical initiatives.

You'll operate within a core priority area in our Next-Generation Soundtracking domain, leading ML/AI teams. A key part of your impact will be to grow, shape, and mentor engineers as we scale our generative AI capabilities. You will manage dependencies and collaborate closely with our data platform, MLOps and product engineering teams to integrate these powerful ML solutions into our end-user experiences.

Your key responsibilities include

• Own the technical roadmap and model strategy for generative music, including diffusion and transformer-based approaches.
• Lead the full lifecycle from research to production, championing training, evaluation, and deployment for real-time inference.
• Drive the productionisation of inference through model optimization (distillation, quantization), caching, and cost controls.
• Build and maintain team health through effective rituals, 1:1s, and fostering a psychologically safe, high-ownership culture.
• Manage cross-team dependencies and delivery with data, MLOps and product engineering teams.

Requirements

• Deep ML engineering background with hands-on experience in generative diffusion models for audio/music (including PyTorch and modern training stacks).
• Proven experience deploying ML systems into production at scale, with a focus on latency, stability and cost.
• Strong ML system design and architecture skills across the full machine learning lifecycle.
• Track record of managing engineering teams
• Demonstrated ability to set clear goals, manage performance and grow engineers through mentorship and feedback.

Equal opportunity employer

We believe that bringing people together from different backgrounds, experiences and perspectives makes for a healthy workplace, a more successful business and a better world. We value diversity and encourage everyone to come and soundtrack the world with us.

Application

Ready to make the world feel your work? Please apply, in English, by clicking the link below.

Thinking about joining us? Tune in with our CEO - and see if we sound like your kind of vibe!