BeatStars is the world’s leading music creator platform, supporting over 10 million creators globally. They are seeking a Research Engineer to develop and deploy machine learning pipelines, scale research into products, and contribute to AI-driven music creation tools.
Responsibilities:
- Building and deploying ML pipelines into production that power real creator workflows
- Scaling ML research into products used by millions of artists and producers
- Leading your own research initiatives from idea → prototype → production
- Optimizing, improving, and maintaining high-performance ML systems
- Working daily in a small, highly collaborative team across Product, Engineering, and ML
- Contributing to the next generation of AI-driven music creation tools
Requirements:
- PhD (or equivalent experience) in Machine Learning, especially around building and deploying ML models in scalable production environments
- Demonstrated experience shipping ML features that are actively used by customers, not just prototypes or notebooks
- Experience training, evaluating, and deploying models end-to-end (data preprocessing → training → validation → inference → monitoring)
- Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX)
- Experience designing scalable inference systems (batch and/or real-time) and optimizing for latency, throughput, and cost
- Familiarity with distributed training, model versioning, experiment tracking, and reproducible pipelines
- Publications or conference participation (e.g., ISMIR, ICASSP, NeurIPS, ICLR, ICML, etc.)
- Background in music tech, audio ML, or generative models
- Experience with research labs (e.g., UPF, CCRMA, CMU, GTCMT, IRCAM, etc.)
- Experience working in ML-first or research-driven environments with a strong culture of experimentation