Founding Edge ML Engineer - Acoustic Sensing

What the Tech, Bend; Bend (OR); Hybrid; USD 120,000 - 170,000; Full time

Job summary

RADD Co is seeking a Machine Learning Engineer to own acoustic models from digitization to edge-triggered results, enabling robust operations in field environments.

You will drive full lifecycle ML: data collection, labeling, feature engineering, model design, training, evaluation, and monitoring, with a focus on edge-friendly architectures and tooling for automated testing and deployment.

Qualifications

• 5+ years of experience building and deploying machine learning models.
• Expert-level proficiency in Python and Keras (or similar).
• Experience with low-power, low-memory edge architectures and frameworks (e.g., TFLite, TensorRT, QaT).
• Experience building automated pipelines for model validation, data selection, and experiment tracking.
• Data curation and feature engineering as core engineering discipline, coordinating with Operations.
• Preferred: real-time filters and frequency-domain features for acoustic/time-series data.
• Geospatial data and telemetry experience for model validation or labeling workflows.
• Estimation/localization on noisy sensor data (location, compass or IMU).

Responsibilities

• End-to-end ML lifecycle: data collection/labeling, EDA, feature engineering, model architecture, training, evaluation, and monitoring.
• Edge-first development: optimize architectures for low-power, low-memory edge devices.
• Develop models for signal classification and estimation using acoustic time-series and sensor data.
• Collaborate with Operations to define and codify our ODD into a data ontology; ensure site-agnostic generalization.
• Evolve ML stack and tooling for data curation, automated model building, cloud-based training, and automated testing of model performance.
• Own infrastructure automation and pipelines for model validation, data selection, and experiment tracking.

Skills

Python

Keras

Edge ML

Model deployment

Tools

TensorRT

TFLite

QaT

Job description

RADD Co is seeking a Machine Learning Engineer to own acoustic models from digitization to edge-triggered results, enabling robust operations in field environments.

You will drive full lifecycle ML: data collection, labeling, feature engineering, model design, training, evaluation, and monitoring, with a focus on edge-friendly architectures and tooling for automated testing and deployment.