Full-Stack Software Engineer & Scientist (Virtual Sensing)

GE Vernova is building the foundation for next-generation decentralized grid operations. As a Full-Stack Software Engineer & Scientist (Virtual Sensing), you will develop edge-native software, advanced virtual sensing algorithms, and intelligent control systems that enable autonomous and adaptive grid management.

Responsibilities:

• Build and deploy edge-native software components for decentralized operation, sensing, and control
• Develop federated data pipelines that allow distributed nodes to collaborate securely without central coordination
• Develop and deploy robust virtual sensing algorithms to infer critical power grid parameters (e.g., voltage stability, phase angles, line temperature, asset health) from limited sensor data available at the grid edge
• Deploy adaptive edge intelligence and control logic at the edge, enabling real-time grid intelligence with minimal latency and network
• Collaborate with power systems engineers to validate virtual sensor accuracy against physical models and real-world data from substations, field devices, and peer sensors
• Integrate field data sources (SCADA, PMUs, DER controllers) and IoT protocols/networks (LoRa, MQTT, DNP3, Modbus)
• Support experimentation and prototyping in simulation environments and customer’s test sites
• Collaborate with systems and data engineers to close the loop between simulation and live operations
• Collaborate with cross-functional teams to integrate AI/ML capabilities, federated control frameworks, and digital twins into next-generation grid platforms
• Work closely with data scientists, control engineers, infrastructure specialists and Customers, to integrate software with physical grid systems

Requirements:

• Working experience with Transmission and distribution, and federated architectures, and resilient edge software
• Strong skills in script writing using MATLAB, Go, Rust, Python (backend/edge) and HTML, CSS, TypeScript/React or Angular(UI)
• Deep Experience with Kubernetes/K3s, Kafka/NATS, MQTT, gRPC, PulsarInfluxDB/TimescaleDB, and observability stacks (Prometheus, Grafana)
• Solid understanding of control theory and signal processing techniques for application in virtual sensing systems, such as Kalman filters or other state estimation methods
• Experience in integrating virtual sensor outputs into existing control loops for real-time monitoring, process optimization, and predictive maintenance applications
• Ability to evaluate and test the performance and reliability of developed virtual sensors
• Skilled in interpreting complex sensor data outputs and translating insights into actionable virtual sensor models
• Work experience with Digital Twin / Simulation modeling: OpenFMB, Modelica, graph-based modeling) and AI/ML model algorithms
• Hands-on work with AI/ML models in production environments
• Work experience in federated architectures, and resilient edge software applied to Transmission & Distribution application
• Bachelor's degree electrical engineering or computer science with a minimum of 5 years' experience in the power or industrial system domain
• Minimum 3+ years of hands-on experience in building real-time or simulation-based system
• Proven experience in software engineering with, Automation, distributed/federated data processing
• Track record of building, deploying, and scaling complex software systems
• Familiarity with grid operations, DER management, and industrial IoT/IIoT
• Experience with real-time or cyber-physical systems requiring low latency and high reliability
• Knowledge of grid standards or protocols (e.g., IEEE 2030.5, IEC 61850, OpenFMB) is a strong plus
• Familiarity with power system modeling and simulation tools such as EMT platforms (e.g. PSCAD, RTDS, Opal-RT) is a plus