• Conduct original research in generative AI for professional creative workflows across image, video, 3D, vector graphics, and design. • Develop new methods that advance the state of the art while remaining relevant to real creative and production workflows. • Publish research at leading academic venues where appropriate, while also contributing to high-impact internal projects. • Explore multimodal generative systems that integrate image, video, 3D, vector graphics, and design, with an emphasis on controllability, editability, and reusable asset creation. • Translate research insights into prototypes, experiments, and model capabilities that can inform product direction. • Work with researchers, engineers, designers, and product teams to identify important research problems with meaningful downstream impact. • Design datasets, benchmarks, and evaluation protocols for professional workflows where quality, editability, consistency, brand adherence, and production usefulness matter. • Stay at the frontier of generative media research and identify opportunities to combine ideas across computer graphics, vision, language, video, and creative tooling. • Contribute to a research culture that values technical depth, intellectual breadth, publication quality, and practical relevance.

• Conduct groundbreaking research in generative audio using diffusion or flow matching models • Run large-scale experiments with access to Spotify's infrastructure and audience • Create practical applications harnessing generative technologies • Collaborate with a cross-functional team to craft innovative solutions • Engage with the broader research community by publishing findings and delivering talks

• 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. • 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.

• Join Prolific's Integrity team, which protects the platform from fraud and misuse • Help shape the role and create structure where there isn't much yet • Spot problems worth solving and start on them, rather than waiting to be assigned • Collaborate with others