Songscription — Founding Music AI Engineer

• →Building and shipping ML models for audio and symbolic music understanding into production systems used by real musicians
• →Translating the research team's ideas into solid, working engineering implementations
• →Partnering with data, design, and product to integrate models into user-facing features
• →Curating, preprocessing, and building pipelines around large-scale music datasets
• →Contributing to model evaluation, optimization, and deployment for real-world latency and reliability

Tech stack: Python, PyTorch / JAX, large-scale ML systems

• Zero to four years of experience in ML engineering, infrastructure, or a comparably demanding technical role
• Time at a company known for a high technical bar — for example, big-tech infrastructure, quant, or a fast-scaling startup
• Strong software engineering and hands-on coding ability
• A track record of building and training ML models, whether in production systems or through substantial hands-on projects
• A bachelor's or master's in computer science, electrical engineering, or a closely related technical field
• Working proficiency with modern ML frameworks such as PyTorch or JAX
• The ability to take research concepts and turn them into robust, shippable code
• A collaborative working style that meshes well with researchers and fellow engineers
• Based in San Francisco (or ready to relocate) and comfortable working in person for the majority of the week

• Prior experience at a startup or other early-stage company
• Exposure to audio, sequence modeling, or generative model domains
• Experience building data pipelines or working with large-scale datasets

• Location — San Francisco, CA
• Work policy — On-site; in person the majority of the week
• Compensation — $175K–$225K + equity
• Visa sponsorship — Open to visa transfers (e.g. OPT, H-1B transfers)
• Employment type — Full-time