Member of Technical Staff - Quantitative Research
Pioneers quantitative research for music generation AI using proprietary datasets, designs evaluation frameworks for models, drives data roadmaps, and builds production infrastructure at the intersection of research, engineering, and product. Requires PhD or 5+ years quant experience with strong coding skills.
About the job
What You’ll Do
- Design & own evaluation/optimization frameworks for frontier music models
- Dive deep under the hood of our music generation systems, applying computational & human resources to understand model capabilities and identify areas for growth
- Build optimization loops and apply your findings to our pretraining, post-training and inference systems as applicable
- Drive product & research roadmap
- Own our data roadmap end-to-end, formulating research questions, exploring/linking/expanding data sources and conducting experiments at your discretion
- Work spans data mining, machine learning, causal inference, survey design and more
- Build stable infrastructure
- Manifest work in robust integrations with our research & product tech stacks, potentially in performance-critical paths
- Build large-scale standalone data processing systems
- Champion scientific rigor
- Cultivate a culture of scientific rigor across the company and deepen common understanding of models, users and data
- Proactively identify opportunities, define metrics, share results, and build a rigorous foundation
What We’re Looking For
- Deep quantitative expertise: Ph.D. in statistics, mathematics, physics, or another quantitative discipline, or 5+ years’ industry experience as a quantitative analyst / data scientist
- Autonomy & ownership: Thrive in greenfield research domains, undefined product categories and small, flat teams
- Engineering chops: Adept in translating your ideas into clear, production-ready code and collaborating in an active research codebase
- Excellence in scientific communication: Relate technical information with rigor and crystal clarity to researchers, engineers, product managers and business partners alike
Nice to Have
- Obsession with music & the science of sound. Experience in DSP, MIR, music production / composition / performance
- Familiarity with deep learning frameworks, especially JAX
- Experience with GCP, Apache Beam/DataFlow, Kubernetes, TensorFlow Data / TFRecord
- Experience designing evaluation frameworks specifically for generative model outputs in any modality
Compensation
- Salary range: $250k - $350k
- Equity and benefits
Skills
JAX, GCP, Apache Beam, Kubernetes, TensorFlow, Dataflow, Tfrecord, Dsp, Mir, Machine Learning, Causal Inference, Data Mining
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