Role OverviewBoston Dynamics is looking for a
Senior Staff Audio Machine Learning Engineer to join the Spot Sensing team. In this role, your core mission will be driving the evolution of our Acoustic Change Detection (ACD) capability-taking beamformed and raw audio and turning it into actionable machinery prognostics.
While
acoustic intelligence is your primary domain, mechanical inspection on Spot is multimodal. Beyond mastering the audio pipeline, you will contribute to the integration of acoustic features with complementary modalities, such as image, video, and thermal, fusing multimodal representations with LLMs/VLMs to empower our end users with prescriptive maintenance actions, not indecipherable data.
You will leverage the world's largest fleet-gathered industrial sensor dataset, utilizing Spot equipped with the Sorama L642 acoustic camera and SpotCAM2.
Key Responsibilities- Acoustic ML & DSP Ownership (Core Focus): Design, refine, and scale digital signal processing and machine learning pipelines for our Acoustic Change Detection (ACD) system.
- Anomaly Detection & Failure Classification: Lead the improvement and modernization of our acoustic detection stack-transitioning from unsupervised models (e.g., BGMM) to state-of-the-art anomaly architectures, and architecting our end-to-end supervised multimodal pipelines for automated fault diagnosis.
- Multimodal Integration & Prescriptive Maintenance: Partner with the broader Spot Apps organization to integrate acoustic insights with visual, thermal, and VLM/LLM data streams into unified machine health indicators, delivering both clear mechanical diagnoses and recommended corrective actions to plant operators.
- Industrial Deployment & Verification: Benchmark, optimize, ship, monitor, and continuously improve our solution for our industrial customers.
Qualifications & RequirementsExperience & Domain Expertise- Experience: 7+ years of deep practical expertise in audio feature extraction, audio fingerprinting (e.g., Shazam, DMCA enforcement) and segmentation (e.g., DCASE), machine learning applied to audio data (beamformed and raw), preferably in industrial environments or another domain with similar problems, for the purposes of anomaly detection.
Technical Skills & Hardware- Languages & Core Tooling: Advanced proficiency in Python and C++, with mastery of numerical and scientific stacks (e.g., NumPy, SciPy, scikit-learn, PyTorch).
- Acoustic Processing: Expertise in time domain and frequency domain data analysis.
- Array Processing: Expertise in multi-channel array processing, including beamforming (Delay-and-Sum, MVDR, null-steering), Direction of Arrival (DoA) estimation, and synthetic aperture techniques.
- Machine Learning & Modeling Paradigms: Expertise in unsupervised and supervised classification architectures for anomaly detection in real-world conditions.
Bonus Points- Hands-on experience in cross-modal fusion (combining audio representations with computer vision, thermal imaging, or multimodal foundation models/VLMs).
- Background in rotating machinery health monitoring (bearings, gearboxes, pumps) and familiarity with mechanical vibration/acoustic failure standards.
- Familiarity with TypeScript/modern web services for integrating your work into Orbit, our fleet management software.
We are interested in every qualified candidate who is eligible to work in the United States. However, we are not able to sponsor visas for this position.
The base pay range for this position is between $180,000 to $220,000 annually. Base pay will depend on multiple individualized factors including, but not limited to internal equity, job related knowledge, skills and experience. This range represents a good faith estimate of compensation at the time of posting. Boston Dynamics offers a generous Benefits package including medical, dental vision, 401(k), paid time off and a annual bonus structure. Additional details regarding these benefit plans will be provided if an employee receives an offer for employment.
