Research Engineer — Agentic Audio ML Workflows
Core
Develop novel AI-powered audio processing algorithms and build agentic tools to automate audio ML research workflows.
Role type
Research Engineer (Agentic Audio ML Workflows)
Builds
Agentic workflows for orchestrating training, evaluation, experimentation, and reporting of audio ML models.
Domain
Audio technology + Machine Learning
Deliverable
production ML models
Required skills
Python, LLM agents, agentic workflows, ML training pipelines, PyTorch, on-prem Linux GPU operations, audio ML/DSP
Preferred skills
Orchestration frameworks, distributed training, CI/CD, MLOps
Technologies
PyTorch, LLMs, Linux, CUDA, containers
Responsibilities
Design and implement agentic workflows to plan, launch, monitor, and summarize audio ML experiments; Automate data preparation, model training, hyperparameter searches, and benchmarking; Build tooling for GPU scheduling, experiment tracking, and reproducible execution; Connect LLM-powered agents to compute resources and evaluation suites; Partner with researchers to create reusable workflows and dashboards.
