Model building: architect, pre-train, fine-tune, and align large-scale speech models.
Project leadership: lead small research projects; collaborate on larger initiatives.
Experimental design: design, run, and analyze experiments to advance models.
Tool development: build and improve dev tooling to boost productivity.
Full-stack contribution: work across the stack from low-level ops to model design.
Data ownership: define data needs and oversee acquisition, labeling quality, and synthetic data.

🎯 Requirements

Extensive R&D with large-scale audio models (>3B parameters, >500k hours data).
Experience with transformers and/or diffusion models and audio language modelling.
Multi-node, multi-GPU distributed training experience.
Proven software engineering track record building complex systems.
Proficiency in PyTorch; performance work (profiling, CUDA/Triton/C++) and production code.
Shipped large-scale speech/audio models to production.

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