Senior Staff Audio Machine Learning Engineer

Sourced from bostondynamics.wd1.myworkdayjobs.com

Boston Dynamics seeks a Senior Staff Audio Machine Learning Engineer for the Spot Sensing team to drive the evolution of Acoustic Change Detection, turning beamformed and raw audio into actionable machinery prognostics. The role owns the acoustic ML and DSP pipeline while integrating audio with visual, thermal, and VLM/LLM data streams for prescriptive maintenance. You will work with the world's largest fleet-gathered industrial sensor dataset using Spot equipped with the Sorama L642 acoustic camera and SpotCAM2.

• Design, refine, and scale DSP and ML pipelines for the Acoustic Change Detection system
• Modernize the acoustic detection stack from unsupervised models to state-of-the-art anomaly architectures
• Architect end-to-end supervised multimodal pipelines for automated fault diagnosis
• Integrate acoustic insights with visual, thermal, and VLM/LLM data streams into unified machine health indicators
• Benchmark, optimize, ship, monitor, and continuously improve solutions for industrial customers

• 7+ years of practical expertise in audio feature extraction, audio fingerprinting, and segmentation
• Machine learning applied to audio data (beamformed and raw) for anomaly detection
• Advanced proficiency in Python and C++, with NumPy, SciPy, scikit-learn, and PyTorch
• Expertise in time-domain and frequency-domain data analysis
• Expertise in multi-channel array processing including beamforming, DoA estimation, and synthetic aperture techniques
• Expertise in unsupervised and supervised classification architectures for anomaly detection

• Cross-modal fusion combining audio with computer vision, thermal imaging, or multimodal foundation models/VLMs
• Background in rotating machinery health monitoring (bearings, gearboxes, pumps)
• Familiarity with mechanical vibration/acoustic failure standards
• Familiarity with TypeScript and modern web services