Music Generation Researcher

Moises is a fast-growing Series A startup with over 60 million users in 190+ countries, named Apple’s iPad App of the Year in 2024. We're hiring two experienced full-time researchers to help push the boundaries of conditional music generation. We’re a music-tech startup that builds tools to empower musicians and producers, not replace them. Our goal is simple: use AI to amplify human creativity, not automate it.

If you’re excited about music, audio, and generative models, and you like the idea of your work ending up in the hands of real creators, you’ll fit right in.

About the role
You’ll be part of a small but mighty R&D team exploring how AI can support music creation. This means researching and building models that generate or transform music based on meaningful inputs: stems, prompts, lyrics, symbolic structures, or anything else that helps musicians express ideas faster.

You’ll take ideas from early experiments to polished systems that can be used in real creative workflows in high-profile products. Expect a mix of research, prototyping, listening, iterating, and plenty of collaboration with people who care deeply about music.

What you’ll do
• Explore and develop new approaches to conditional music generation.
• Build, train, and evaluate novel music gen architectures using large audio datasets.
• Collaborate with ML engineers, audio folks, and product teams.
• Turn research breakthroughs into tools musicians can actually use in their day-to-day.
• Keep up with the latest in generative modeling and audio ML, and participate in the scientific community.

What we’re looking for
• Experience with generative models (diffusion, transformers, autoregressive, etc.)
• Strong machine learning and deep learning fundamentals
• Solid programming skills in Python and experience with PyTorch
• Several years of experience working on ML research or applied research
• Comfort working with large-scale training and experimentation
• Curiosity about music, sound, and creative workflows
• Ability to explain complex ideas clearly and work well with others

Nice to have
• Experience with conditional generation tasks
• Background in music production, DSP, or audio engineering
• Publications or open-source contributions in audio or ML
• Experience shipping research into real products

What it’s like to work here
We’re a small team with big musical energy. We care about craft, experimentation, and listening deeply. You’ll be working with people who obsess over both loss curves and snare sounds. We’re fully remote, flexible, and driven by a mission to build technology musicians actually want to use. You’ll have room to try things, ask questions, and push the state of the art. Check out what we’ve been up to here.

Compensation and benefits
• Competitive pay
• Flexible paid time off
• Paid parental leave
• Monthly wellness stipend Learning

• Learning and development support for conferences, courses, and training

How to apply
Send us your resume, anything you’ve built or written that you're proud of, and a short note on why music AI matters to you (and feel free to share links, demos, or stories). We review applicants as they come in.