Conduct groundbreaking research in generative audio using diffusion or flow matching models, with a focus on one or more of the following areas:
Vocal Synthesis — Research in vocal and speech synthesis, along with related areas such as ML-based audio processing and signal processing.
Post-Training — Research in post-training techniques for music generation, including preference alignment methods (such as DPO, RLHF, or KTO), reward model design and training, and reinforcement learning to improve output quality, controllability, and human preference adherence.
Editing — Research in iterative music generation and audio editing, including capabilities such as stem replacement, instrumentation change, mood changes (while preserving content), tempo changes, and structure changes.
You have a Ph.D. in Computer Science, Mathematics, Engineering, or a related field. Previous industry experience is helpful.
You have experience in one or more of the following fields: generative modeling, machine learning, music information retrieval, speech processing, audio processing, signal processing, probabilistic modeling, computer vision, or related areas.
You have deep expertise in at least one of the focus areas above—whether that's vocal/speech synthesis, post-training alignment techniques (e.g., PPO, GRPO, DPO), or audio-to-audio generation and text-guided music editing.
You have publications at leading conferences such as ICASSP, ISMIR, INTERSPEECH, ICLR, AAAI, IJCAI, NeurIPS, ICML, CVPR, ECCV, ICCV, or related venues.
You have strong coding skills in Python, PyTorch, and NumPy.
You are a creative problem solver who is passionate about building outstanding products that add real value to millions of people.
You are enthusiastic about turning research ideas into products operating at scale.
You can explain complex topics in simple terms, and you enjoy building strong relationships with colleagues and stakeholders.
Taken from the listing. Check the full advert before you apply.
Full description
We are seeking Research Scientists (across all levels of seniority) to join our Artist-First AI Music Lab. Our team pioneers and advances state-of-the-art generative technologies for music that create breakthrough experiences for fans and artists. We invent entirely new listening experiences that center and celebrate artists and creatives. All of our products will put artists and songwriters first, through these four principles:
Partnerships with record labels, distributors, and music publishers: We’ll develop new products for artists and fans through upfront agreements, not by asking for forgiveness later.
Choice in participation: We recognize there’s a wide range of views on the use of generative music tools within the artistic community. Therefore, artists and rightsholders will choose if and how to participate to ensure the use of AI tools aligns with the values of the people behind the music.
Fair compensation and new revenue: We will build products that create wholly new revenue streams for rightsholders, artists, and songwriters, ensuring they are properly compensated for the use of their work and transparently credited for their contributions.
Artist-fan connection: AI tools we develop will not replace human artistry. They will give artists new ways to be creative and connect with fans. We will leverage our role as the place where more than 700 million people already come to listen to music every month to ensure that generative AI deepens artist-fan connections.
Conduct groundbreaking research in generative audio using diffusion or flow matching models, with a focus on one or more of the following areas:
Vocal Synthesis — Research in vocal and speech synthesis, along with related areas such as ML-based audio processing and signal processing.
Post-Training — Research in post-training techniques for music generation, including preference alignment methods (such as DPO, RLHF, or KTO), reward model design and training, and reinforcement learning to improve output quality, controllability, and human preference adherence.
Editing — Research in iterative music generation and audio editing, including capabilities such as stem replacement, instrumentation change, mood changes (while preserving content), tempo changes, and structure changes.
You will also:
Run large-scale experiments with access to Spotify's extensive infrastructure and an audience of more than 700 million monthly active users.
Create practical applications that harness generative technologies and push the boundaries of what's possible in listening experiences.
Collaborate as part of a cross-functional team—working closely with scientists, engineers, product managers, designers, user researchers, and analysts—to craft innovative solutions to complex challenges.
Have a direct impact on Spotify's products, tools, and services, working on projects that influence the entire organization.
Engage with the broader research community by publishing your findings, delivering talks, and attending top conferences.
Who You Are
You have a Ph.D. in Computer Science, Mathematics, Engineering, or a related field. Previous industry experience is helpful.
You have experience in one or more of the following fields: generative modeling, machine learning, music information retrieval, speech processing, audio processing, signal processing, probabilistic modeling, computer vision, or related areas.
You have deep expertise in at least one of the focus areas above—whether that's vocal/speech synthesis, post-training alignment techniques (e.g., PPO, GRPO, DPO), or audio-to-audio generation and text-guided music editing.
You have publications at leading conferences such as ICASSP, ISMIR, INTERSPEECH, ICLR, AAAI, IJCAI, NeurIPS, ICML, CVPR, ECCV, ICCV, or related venues.
You have strong coding skills in Python, PyTorch, and NumPy.
You are a creative problem solver who is passionate about building outstanding products that add real value to millions of people.
You are enthusiastic about turning research ideas into products operating at scale.
You can explain complex topics in simple terms, and you enjoy building strong relationships with colleagues and stakeholders.
Where You'll Be
We offer you the flexibility to work where you work best! For this role, you can be within the EMEA region as long as we have a work location
This team operates within the Central European and GMT time zone for collaboration.
Core working hours are CET 3pm-6pm / EST 9am-12pm.
Sourced from the employer’s own listing · last verified 10 Nov 2026. Report this listing