Signal-based fault detection and localization for utilities, critical infrastructure, and high-risk environments. Reduce ignition risk. Accelerate response. Protect what matters.
“GridIQ, a startup using intelligent sensors to detect and isolate electrical faults in real time, aiming to stop wildfires before they start.”
Utilities and critical infrastructure operators lack real-time situational awareness at the edge of the grid—where faults happen, fires ignite, and outages cascade.
Arcing, conductor contact, and equipment failures on distribution lines are a leading cause of catastrophic wildfires.
Most ignitions escalate within seconds. Legacy systems detect faults too slowly—or not at all—to prevent fire spread. GridIQ classifies anomalies in milliseconds.
Knowing a fault occurred isn't enough. Crews need meter-level accuracy across miles of conductor to respond before conditions worsen.
Wildfire liability, PSPS events, and regulatory pressure are forcing utilities to modernize faster than ever.
GridIQ deploys patent-pending, signal-based sensors that continuously monitor distribution infrastructure. We detect faults, localize them with precision, and deliver actionable insights—so you can act before conditions escalate.
Instantly categorize fault types—arcing, contact, equipment failure—within milliseconds for faster, smarter deployment decisions.
A single sensor monitors up to one mile of conductor with meter-level accuracy to pinpoint exactly where faults occur.
Continuous monitoring with instant alerts to operations and field crews—know what's happening before it escalates.
Integrates with existing infrastructure—poles, reclosers, and aging equipment.
GridIQ was built for the most demanding environment: high fire-threat districts where seconds determine whether a fault becomes a catastrophe.
Identify arcing, incipient faults, and conductor anomalies before they escalate to fire.
Provide operations teams with the confidence to act quickly—reducing PSPS scope and duration.
Guide field crews to the exact location, minimizing search time in high-risk terrain.
Capture high-fidelity event data for regulatory reporting and continuous improvement.
The same precision that prevents wildfires delivers value across critical infrastructure, resilience applications, and emerging electrification corridors.
From sensing to action—a continuous loop of grid health intelligence
Sensors continuously monitor electrical signatures across your distribution network, identifying anomalies and fault conditions in real time.
Proprietary signal analysis pinpoints fault location with meter-level precision—no dense sensor arrays or line-of-sight required.
Cloud analytics classify fault type and severity, correlating with environmental and operational context for actionable insight.
Alerts push instantly to your real-time dashboard, mobile crews, and enterprise systems—enabling rapid response before conditions escalate.
Purpose-built hardware, cloud analytics, and integrations—designed for utility-grade reliability and enterprise deployment.
Ruggedized, pole-mounted devices with cellular connectivity. Designed for harsh environments and rapid deployment.
Scalable signal processing and fault classification. Real-time dashboards and historical trend analysis.
Configurable thresholds and notification rules. Push to email, SMS, webhook, or enterprise alerting systems.
APIs and connectors for OMS/DMS, GIS, and work management platforms.
We understand that utilities and critical infrastructure operators require rigorous data protection. Security is foundational to how we build and operate GridIQ.
We work with utilities and critical infrastructure operators on problems that matter. When roles open, they will appear here.
Hybrid – Full-time · San Francisco, CA | Los Angeles, CA | Seattle, WA | Remote
You will own the power and energy subsystem for our edge devices, including battery management, PMIC rail distribution, and overall power budgeting. This is a hands-on individual contributor role at a small company. You will take designs from schematic to bench to field.
Our edge device lives outdoors, exposed to weather, and minimally accessible after installation. You will own the enclosure and mechanical integration, device mounting, and support electrical design for non-RF subsystems. This role bridges mechanical and electrical work.
Hybrid – Full-time · San Francisco, CA | Los Angeles, CA | Seattle, WA | Remote
You will own firmware for GridIQ's edge device: low-power state management, RF acquisition scheduling, cellular data transport, OTA updates, and production test firmware. The device operates autonomously in the field for months. You will collaborate with hardware engineering on board bring-up and with the platform team on the device-to-cloud protocol.
Hybrid – Full-time · San Francisco, CA | Los Angeles, CA | Seattle, WA | Remote
The RF front-end is the core of GridIQ's edge device sensing chain. You will own the custom front-end PCA from architecture through first-article: schematic capture, PCB layout direction, signal integrity simulation, and DFM hand-off to manufacturing. This is hands-on design work.
You will design and build the cloud platform for GridIQ's grid monitoring device — device data ingestion over MQTT/HTTPS, time-series storage, multi-tenant access control, alerting, data backup, and the API consumed by the operator dashboard. This is a greenfield build designed to work for a pilot and scale to a multi-thousand device fleet without re-platforming.
Hybrid – Full-time · San Francisco, CA | Los Angeles, CA | Seattle, WA | Remote
We are looking for an Applied AI/ML Engineer to own the full analytical stack from raw sensor data to actionable grid intelligence. This is not a benchmark dataset problem — the data comes from physical systems operating in complex, variable environments. You will be the technical owner of how GridIQ turns edge data into operational insights.