Senior ML Engineer, Multi-Sensor Modeling

Develop algorithms that improve the speed, accuracy, and reliability of Gridware’s automated hazard detection systems

Work with multimodal time-series and spatial sensor data across diverse sampling rates and noise characteristics.

Design models that are robust, interpretable, and deployable in production environments.

Live in the data; help curate & share strategic & well-defined datasets that help solve our highest-value challenges

Explore advanced approaches such as graph-based learning for grid topology reasoning, geospatial modeling and localization and multimodal fusion across acoustic, magnetic, vibration, electrical, and visual signals

Production Engineering

Write clean, scalable, well-tested Python code that integrates into a large shared codebase.

Build end-to-end ML pipelines including data processing, feature extraction, training, evaluation, and deployment.

Optimize models for performance, reliability, and real-world constraints.

Collaborate on infrastructure for model monitoring, validation, and continuous improvement.

Collaboration & Communication

Translate complex analyses into clear insights for engineers, operators, and leadership.

Frame solutions to ambiguous, open-ended problems to achieve buy-in from various stakeholders by focusing on the business impact of your projects

Communicate uncertainty, tradeoffs, and model behavior effectively.

Partner cross-functionally with software, data engineering, product, and event-reporting teams.

Help shape technical direction and best practices for ML at Gridware. This includes exemplifying standards for experiment tracking, model versioning, reproducibility, and lifecycle management.