WHO WE ARE

Founded in 2023 by music industry veteran Matthew Adell, serial startup founder Sean Power, and Machine Learning expert Nicolas Gonzalez Thomas, Musical AI builds technology that makes training on copyrighted content both possible and principled. We have invented verifiable attribution technology that measures the influence of an AI training corpus on generative AI outputs. Our platform includes a licensing layer that connects AI builders with premium copyrighted catalogs under clear terms, so AI companies can move fast in ways that work positively within the entertainment industries.
We partner with AI companies, labels and publishers to make consent, credit and compensation practical at scale. To learn more about us, read our full Manifesto (https://www.wearemusical.ai/Manifesto). We are backed by incredible VCs who understand our vision and support us in execution. This is your chance to join from the ground floor, help shape our product, and leave your mark on something that will change the music industry forever.
We’re first-to-market in our category because we move fast, thoughtfully experiment, and balance innovation with practical delivery. We have a big idea and we need a team that can help us get it done. Our values define how we work: innovation, adaptability, accountability, collaboration, urgency, and value creation.

WHO WE’RE LOOKING FOR

We’re looking for a curious, collaborative, and impact-driven Principal Machine Learning Engineer who wants to build groundbreaking tools at the intersection of AI and music. As an early team member, you’ll be expected to lean on your experience and get your hands dirty. You don’t have to be a music theory expert, but a commitment to making premium AI training accessible is. We’re looking for someone who thrives in collaborative, inclusive teams where we work together to get things done, and who can adapt easily when things change (and in AI, they change often). Our team values shipping, testing, and improving over chasing perfection, and takes pride in learning, experimenting, and building things that make a difference.
We’re remote-first across Canada and come together as a team a minimum of twice a year. All applicants must live and be eligible to work in Canada.

YOUR EXPERIENCE

• 3-5 years experience in ML systems development, vector search and optimization, production systems, and audio technology
• Background in audio processing libraries (Essentia, librosa), music technology, or related fields preferred
• Hands-on experience with FAISS for large-scale similarity search
• Understanding of embedding space mathematics and dimensionality reduction
• Understanding of musical structures, harmony, rhythm, and composition
• Experience with multi-modal learning (audio, text, symbolic music)
• Experienced in REST API development with Flask/FastAPI for ML model serving
• Experienced in Cloud deployment (AWS/GCP) and containerization
• Experienced in intellectual property, rights management, or legal tech advantageous
• Understanding of music industry workflows and attribution challenges