Research Engineer — Agentic Audio ML Workflows

Bose Corporation develops AI-powered audio processing algorithms designed to run in real time on physical devices. The Research Engineer will build agentic tools and automation to orchestrate audio ML training, evaluation, experimentation, and reporting across on-premises and cloud GPU infrastructure.

Responsibilities:

• Design and implement agentic workflows that plan, launch, monitor, diagnose, and summarize audio ML experiments, with appropriate human oversight
• Automate data preparation, model training, hyperparameter searches, benchmarking, regression testing, and result comparison across research projects
• Build reliable tooling for on-premises GPU scheduling and utilization, experiment tracking, artifact management, and reproducible execution
• Connect LLM-powered agents to scripts, repositories, datasets, evaluation suites, and compute resources through well-defined tools and safeguards
• Partner with audio researchers to turn repetitive experiments into reusable workflows and clear dashboards or reports

Requirements:

• Degree in computer science, machine learning, electrical engineering, or a related field, or equivalent practical experience
• Strong software engineering and Python skills, with hands-on experience building LLM agents or agentic workflows that invoke tools and execute multi-step tasks
• Comfortable tackling complex, open-ended problems where you have to experiment with and discard many ideas before finding the right solution
• Experience with ML training and evaluation pipelines, PyTorch, experiment tracking, and automated testing
• Practical experience operating on-premises Linux GPU machines, including CUDA environments, containers, job scheduling, and resource monitoring
• Working knowledge of audio ML and DSP, including common datasets, audio metrics, and model development workflows
• Ability to build reliable, observable systems and communicate effectively with research scientists
• Experience with orchestration frameworks, distributed training, CI/CD, or MLOps is a plus