Music Generation Researcher at Moises
Interview Preparation Plan
As a Music Generation Researcher at Moises, you will be at the forefront of innovation in AI-driven music creation. This role involves exploring, developing, and implementing novel architectures for conditional music generation. You will work with large-scale audio datasets to train and evaluate models, transforming research breakthroughs into practical tools for musicians and producers. The goal is to amplify human creativity, not automate it, by building AI that assists and enhances the music-making process. This is an opportunity to contribute to a product used by millions worldwide and to shape the future of music technology. This position requires a deep understanding of machine learning, particularly in the domain of generative models. You will collaborate closely with a cross-functional team of ML engineers, audio specialists, and product managers to bring research ideas from conception to production. The role demands a blend of rigorous scientific inquiry, hands-on development, and a passion for music and sound. You will be expected to stay current with the latest advancements in generative modeling and audio ML, and to actively participate in the scientific community.
Key Responsibilities
- Explore and develop new approaches to conditional music generation.
- Build, train, and evaluate novel music generation architectures using large audio datasets.
- Collaborate with ML engineers, audio experts, and product teams to translate research into usable tools.
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