Neara builds a physics-enabled digital twin of utility networks, combining LiDAR and GIS data with an ML stack spanning PyTorch, TensorFlow and JAX. A near-even split between engineering and sales hiring, heavy on director-level roles, points to a company shifting from product build-out to commercial scale. Expansion spans India, Europe, the US and Asia-Pacific. Job posts center on getting utilities to adopt and deploy the platform rather than on core R&D.
Notable leadership hires: Tech Lead, Commercial Director, ABM Director, PMO Director, Product Director
Neara is a Sydney-based software company founded in 2016 that models utility infrastructure as a geometrically precise digital twin. Utilities and other infrastructure owners use it for simulation, pole loading and line design analysis, storm hardening, wildfire mitigation and investment prioritization. The platform draws on LiDAR and GIS data, with data pipelines built on Snowflake, BigQuery, Databricks, dbt and Airflow, running on AWS. The privately held company employs 201–500 people. It hires across Australia, the United States, the United Kingdom, Germany, the Netherlands, India, Singapore and China.
Neara uses Python, TypeScript, Rust, C++ and Dart, with PyTorch, TensorFlow and JAX for ML. Its data stack includes Snowflake, BigQuery, Databricks, dbt and Airflow on AWS, plus GIS tools such as QGIS, ArcGIS and FME.
Neara is headquartered in Sydney, New South Wales, Australia. It also hires in the US, UK, Germany, the Netherlands, India, Singapore and China.
Yes. Hiring is accelerating, with engineering and sales as the two largest departments. Many openings are at director level, including Commercial Director, ABM Director and PMO Director roles.
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Neara'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.