We’re looking for an AI / ML / MIR Engineer Intern to join our team and help us push the frontier of how machines understand music.
You’ll work with our engineers and music team on developing systems that can analyze, tag, and represent musical stems, teaching Hyph’s platform to understand music the way musicians do.
You might be a fit if you:
Are fluent in Python and comfortable with PyTorch
Understand core machine learning principles and enjoy building things from scratch
Have curiosity or experience in music theory, signal processing, or MIR
Are comfortable with data: organizing, preprocessing, and working with real-world audio datasets
Stay curious and keep up with new developments in ML, audio AI, and generative systems
Bonus points:
Have built or experimented with audio ML models
Have experience with DSP
Play an instrument, produce music, or simply love working with sound
What you’ll do
In one sentence: Teach Hyph to understand music at scale.
Collaborate with the AI and Music teams on research and development projects
Build models to analyze stems (key, mode, tempo, time signature, sections, genre, etc.)
Experiment with representation learning and music understanding systems
Help streamline internal tagging workflows with machine learning
Prototype, test, and document results that feed directly into product development
Our tech stack
Backend: Python, FastAPI
ML: Python, PyTorch
Data: Postgres
Cloud: AWS
Mobile: Flutter
Frontend: Angular (TypeScript)