Engineering
full time

Founding Music AI Researcher/Engineer

San Francisco, CA
$175,000–$225,000 + Equity
Posted October 23, 2025

About Songscription

At Songscription, we are building state-of-the-art AI models that automate music transcription, arrangement, and leveling, with the vision of enabling any musician to learn any song, on any instrument, at any level.

There are over 500 million musicians worldwide; however, 80% of musicians can't play the songs they want because they don't have access to sheet music for their instrument at their level. Additionally, because traditional music education is unaffordable, millions of aspiring musicians never learn how to play. We are here to change that by leveraging recent breakthroughs in AI to make music education more accessible worldwide.

Impact: Over 100K musicians have used us to date, most of whom were looking to transcribe songs that have never been written before.

An Ambitious Goal: We aim to become a standard part of musicians' toolkits and a recognizable name to musicians worldwide.

Large Market: Billion dollar revenue opportunity. Incumbents in space are analog and rely on manual transcription. The space is ripe for disruption which will provide unprecedented access to music education to people worldwide.

If you're excited by the intersection of AI, music, and learning, and want to shape how the next generation of musicians learn, we'd love to hear from you.

Role Description

Songscription is hiring a Founding Music AI Researcher/Engineer to help push the frontier of AI for music creation and education. We are building models that can listen, understand, and ultimately help humans learn music — automating transcription, arrangement, leveling, and performance feedback. You'll work closely with our Head of AI and data, design, and product teams to turn cutting-edge research into production-ready systems that power the next generation of music learning.

This role is ideal for a researcher who wants to see their ideas reach real musicians. You'll prototype new architectures, experiment with large-scale datasets, and ship production models that enable musicians to play, learn, and create in entirely new ways.

Key Responsibilities

  • Research, design, and implement machine learning models for audio and symbolic music understanding and information retrieval
  • Collaborate with design and engineering to integrate models into user-facing products
  • Work with our data team to curate, preprocess, and augment large-scale music datasets
  • Conduct model evaluation, ablation studies, and optimization for real-world latency and reliability
  • Translate recent research advances into applied systems that directly impact creators and learners
  • Play a key role in shaping the direction of our AI roadmap, from early research to large-scale deployment

About You

  • Strong background in machine learning or signal processing, with demonstrated research experience (publications, open-source projects, or significant independent work)
  • Experience building and training large-scale models (audio, sequence, or generative domains preferred)
  • You care about getting models into production and have strong coding and experimentation skills with a practical mindset
  • Comfortable collaborating across disciplines, from engineers to designers and musicians
  • Excited about the intersection of AI and music; performance or composition experience is a plus

Benefits

  • Medical, Vision, Dental, and Life Insurance
  • PTO
  • Team events
  • $175K–$225K + Equity

How to Apply

If you're interested, please email your LinkedIn and resume to jobs@songscription.aiNote for applicants: Be sure to mention pirates or something pirate-related in your email when you apply. We love candidates who read thoroughly!

We are an equal opportunity employer and value diversity at our company. Don't meet all the requirements for the position? That's okay. We encourage you to still apply!

If Songscription isn't right for you but you know someone who might be, send them our way. We're offering a referral bonus to anyone who refers a successful hire.