Offshore wind engineering consultancy covering full project lifecycle
Wood Thilsted designs offshore wind farms from exploration through operation, with a tech stack bridging CAD (Autodesk Inventor, Vault), geospatial tools (ArcGIS Pro, QGIS, Petrel), and data science (Python, TensorFlow, PyTorch, Databricks). The hiring mix is heavily engineering-focused (12 of 14 open roles), with active recruitment across UK, Poland, Japan, and South Korea—signaling expansion into APAC markets. Ongoing projects span foundation design, geotechnical surveys, and in-house software development, while pain points center on design optimization, quality control, and scaling support infrastructure.
Wood Thilsted is an offshore wind engineering consultancy based in London, founded in 2015 and operating as a Certified B Corp. The firm provides end-to-end design and advisory services for offshore wind farms, including geotechnical analysis, foundation engineering, structural design, and owner's engineering support across project phases from pre-auction through operation. The company serves developers and utilities scaling renewable energy assets globally, with active project work on large detailed designs, foundation optimization, and geophysical surveys. Current hiring activity spans 14 roles with acceleration toward mid-market engineering depth and geographic reach into Asia-Pacific.
Autodesk Inventor and Vault for CAD/modeling, ArcGIS Pro and QGIS for geospatial analysis, Petrel for subsurface interpretation, MATLAB for engineering calculations, and Python/TensorFlow/PyTorch for analytics and optimization.
Active hiring in South Korea and Japan signals APAC expansion, alongside existing UK and Poland operations. Pain points explicitly flag market share growth in South Korea as a strategic priority.
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Wood Thilsted'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 →
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