Principal Satellite Image Processing Engineer
1 month ago
About KaleidEO
KaleidEO is investing to launch its fleet of earth observation satellites.SatSure is a deep tech, decision Intelligence company that works primarily at the nexus of agriculture, infrastructure, and climate action creating an impact for the other millions, focusing on the developing world. We want to make insights from earth observation data accessible to all.The synergy of KaleidEO and SatSure aims to bring a new dimension to the earth observation industry by being the only full-stack company from India, to have satellites in space to deliver insights on the ground.
Roles and Responsibilities:
Pipeline Architecture & Development:
Lead the design, development, and implementation of an efficient, scalable image processing pipeline for satellite optical sensor data, from raw data ingestion to analysis-ready outputs.Algorithm Design
: Develop and optimize algorithms for key image processing stages, including radiometric and geometric correction, atmospheric correction, image enhancement, mosaicking, and orthorectification.Data Preprocessing:
Oversee the development of robust preprocessing techniques to handle satellite imagery (noise reduction, calibration, sensor alignment, etc.) for optimal analysis accuracy.Advanced Image Analysis:
Apply cutting-edge techniques such as deep learning, object detection, and spectral analysis to extract meaningful insights from optical imagery (e.g., DEM/DSM, change detection).Integration with Cloud and On-Premise/On-Edge Systems
: Develop and implement solutions for cloud-based processing (e.g., AWS, Google Cloud) or hybrid environments to handle large-scale satellite data efficiently.Automation & Scalability:
Ensure the pipeline is automated, efficient, and scalable to handle high-volume satellite data processing tasks.Team Leadership:
Provide technical leadership and mentorship to a team of engineers and researchers, guiding them through the design and development of components within the processing pipeline.Cross-functional Collaboration:
Work closely with other teams, including data scientists, software engineers, and GIS specialists, to integrate image processing pipelines into broader systems and applications.Quality Control:
Ensure the pipeline delivers high-quality, accurate image products by implementing quality assurance practices and validating outputs against ground truth or reference data.Research & Innovation:
Stay up-to-date on the latest advances in optical remote sensing, image processing technologies, and machine learning applications, and incorporate innovations into pipeline development.Documentation & Reporting:
Maintain thorough documentation of the pipeline architecture, algorithms, processes, and development timelines, and report progress to key stakeholders.
Qualifications:
Advanced degree (Master’s or Ph.D.) in Remote Sensing, Geospatial Science, Electrical Engineering, Computer Science, or a related field.8+ years of experience in satellite image processing, remote sensing, or related fields, focusing on optical sensor data.
Must-Have:
Experience designing and optimizing image processing pipelines for satellite imagery, particularly optical sensors (e.g., multispectral, hyperspectral).Proficiency in image processing and computer vision algorithms (e.g., image correction, enhancement, feature extraction).Expertise in programming skills like Python, C++, or MATLAB, with experience using image processing libraries (e.g., OpenCV, GDAL, scikit-image).In-depth understanding of satellite optical sensors (e.g., Landsat, Sentinel-2, WorldView) and the processing challenges associated with their data.Experience with cloud-based processing platforms (e.g., AWS, Google Cloud, Microsoft Azure) and distributed computing for large-scale data.Experience in leading engineering teams and managing complex technical projects.Familiarity with geospatial data formats and tools (e.g., GeoTIFF, HDF, QGIS, ArcGIS).Understanding of machine learning/deep learning techniques for image analysis (e.g., segmentation, classification, object detection).
Good to Have:
Expertise in atmospheric correction models and radiometric calibration techniques.Experience working with hyperspectral data and advanced spectral analysis techniques.Prior experience with Synthetic Aperture Radar (SAR) processing or integrating optical and radar data.Familiarity with international satellite data sources (e.g., MODIS, Pleiades, SPOT) and commercial data providers.Contributions to open-source remote sensing or image processing projects.Knowledge of high-performance computing (HPC) environments or GPU-accelerated computing for image processing tasks.
Benefits:
Medical Health Cover for you and your family including unlimited online doctor consultations.Access to mental health experts for you and your family.Dedicated allowances for learning and skill development.Comprehensive leave policy with casual leaves, paid leaves, marriage leaves, bereavement leaves.Twice a year appraisal.
Interview Process:
Introductory callAssessmentPresentationInterview rounds (ideally up to 4-5 rounds)Culture Round / HR round
No of positions: 1Expected Month of Joining: as soon as possible.
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