AiDash aims to be a global leader in demystifying artificial intelligence in traditional industrial sectors. We help Fortune 500 companies utilize high-resolution satellite data for inspection and remote monitoring of geographically distributed assets. These assets can be power grids in forests, railway lines in deserts, or construction in or remote terrains. Recommendations for preventive and predictive maintenance generated by our proprietary AI models have helped clients save millions of dollars.
Our team of researchers, engineers, data scientists, geospatial analysts, business consultants, and product managers constantly thrive to build AI models and products, which makes the job of business executives and operating teams easier.
To fuel, our capability and growth plans, we have raised $6 million in a Series A funding round led by Benhamou Global Ventures (BGV) and National Grid Partners (NGP) to give us both strategic and financial boost. In addition to being a well-funded venture, we are a fast-growing, multi-million-dollar revenue company with many Fortune 500 customers.
What you will be doing?
The goal of our engineering team is to build best-in-class SaaS products backed by our proprietary AI models and complex geo-spatial datasets.
As Data Scientist at AiDash, you will be responsible for:
- Research & develop algorithms to model real-world problems using Large Geospatial datasets i.e. Rasters & Vectors. This includes data analysis, feature extractions, spatial-temporal
- Help develop, improve and evangelize our AI/Geospatial knowledge base and
- Design and develop APIs and SDKs for processing Images & Large Geospatial datasets on
- Work cross-functionally with data scientists and data engineers to integrate Machine Learning models into production
- Work with data scientists and data engineers to translate AI-ML algorithms into APIs and SDKs which can run on
- Work with the team to develop and improve the algorithms for enhancing the quality of input datasets
What do you need for this position?
- Ph.D. or MS with industry experience in engineering and related field with a focus on remote sensing and geospatial
- Coding proficiency with geospatial Python packages g., GDAL, RasterIO, Shapely, NumPy, pandas,Tensorflow
- Experience working with a variety of satellite data types (e.g. optical, SAR, Lidar).
- Experience in implementation of AI/ML based models on Images or Geospatial
- Experience in distributed computing for processing Images or Geospatial