Job Description

Computer Vision Engineer

Must-Have: 

• A minimum of 3 years of industrial experience is required. 
• Excellent coding skills in Python and C++.. 
• Good hands-on experience with Computer Vision libraries such as OpenCV, Scikit-Image, and Boost. 
• Knowledge of Geospatial libraries & APIs, including GDAL, RasterIO, GeoPandas, and Shapely, is essential. 
• Experience with Cloud Platforms especially with Amazon AWS and on-prem hardware is must to have. 
• Familiarity with DevOps tools like Docker, Git, and Kubernetes is a plus.
• Strong foundational understanding and experience with various machine learning algorithms and feature reduction techniques. 
• Prior to Deep Learning expertise for semantic and instance segmentation, object detection is a must to have. 
• Hands-on experience and knowledge of Deep Learning libraries, algorithms such as TensorFlow & Keras, PyTorch, FastAI, U-Net, YOLO >= 5, Mask-R CNN, and Segment Anything (SAM) will be considered as a strong asset in the candidate. 
• Familiarity with popular satellite imaging sensors, such as Optical (Maxar, Airbus, Planet, Satellogic, BlackSky, Sentinel-2) and SAR (Umbra, Capella, Sentinel-1) will be considered as a strong asset in the candidate. 
• Strong understanding and familiarity with data science lifecycle practices.
• Knowledge of creating a full-stack application using the MLOps framework will be considered an asset in the candidate.