Next-generation geothermal power development with advanced drilling and subsurface analytics
Fervo Energy builds geothermal power plants engineered for 24/7 carbon-free generation. The stack reveals a heavy operations and controls focus—SCADA, DCS, Rockwell industrial controllers, and OPC UA dominate alongside subsurface modeling tools (Petrel, ArcGIS)—paired with Python-based analytics (NumPy, Pandas, SciPy) for reservoir simulation. Hiring velocity is accelerating across engineering (24 open roles) and finance/ops, with senior and manager-level positions leading the charge, signaling a shift from R&D into repeatable project deployment and cost optimization.
Notable leadership hires: Brand Communications Director
Fervo Energy develops utility-scale geothermal power plants designed to compete on cost with conventional generation while delivering round-the-clock clean power. Founded in 2017 and headquartered in Houston, the company combines geoscience innovation with modern drilling and subsurface analytics to unlock geothermal as a grid-scale resource. Current project work centers on standardizing 50 MW power block designs, reservoir modeling, cost-of-completion estimation, and supply chain consolidation—indicating a transition from prototype toward production deployment. Active pain points include scaling manufacturing, reducing drilling and construction cycle time, and managing supply chain risk across multi-site operations.
Industrial controls (Rockwell ControlLogix, CompactLogix, Studio 5000), SCADA, DCS, and OPC UA for power plant operation. Subsurface work uses Petrel and ArcGIS. Financial tooling includes Workiva, FloQast, and Primavera P6. Analytics stack: Python, NumPy, Pandas, SciPy. Cloud: Azure and AWS.
Houston, Texas. The company was founded in 2017 and currently employs 51–200 people, hiring exclusively in the United States.
Other companies in the same industry, closest in size
Fervo Energy's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.