Position Overview
Our client is building the next generation of AI-powered music creation that transforms prompts, lyrics, and melodies into full songs. As the ML Engineer / Researcher, you will lead efforts to enhance the audio and song quality of generative music models, deploying state-of-the-art architectures (diffusion models, GANs, LLMs) directly into production. This is a Full-Time, On-Site role based in San Francisco, CA with a compensation of $120K – $230K plus Equity.
Key Responsibilities
• Train and improve generative models using PyTorch
• Scale distributed training across multi-GPU infrastructure (H100s)
• Collaborate with engineering to deploy models to production
• Conduct research to improve generative audio quality
• Help build product features powered by your models
Required Qualifications
• 1+ years of experience training diffusion models, GANs, or LLMs in PyTorch
• Experience with distributed training (multi-GPU or multi-node)
• Experience with JavaScript (React/Next.js) and backend development
Preferred Qualifications
• Experience with audio models or music production
• Audiophile-level attention to sound quality
