Image Processing Scientist - Radiometric

Role Radiometric Scientist

Employment Type Full Time

Location Bangalore, India

Educational Qualification PhD or Masters in Remote Sensing, Physics, Electrical Engineering, Optics, or a closely related field.

Work Experience 6+ yrs

Role Description

We are seeking a Radiometric Imaging Scientist to lead the radiometric calibration and characterization of Pixxel's hyperspectral constellation. You will sit at the intersection of sensor physics and product delivery, ensuring that raw detector counts are transformed into high-fidelity, physically meaningful radiance and reflectance products. You will define the protocols for pre-launch and in-orbit calibration to ensure data integrity across the entire constellation.

Responsibilities

• Radiometric Pipeline Ownership: Architect and maintain the radiometric processing chain, including Non-Uniformity Correction (NUC), dark current subtraction, and absolute radiometric scaling.
• Sensor Characterization: Analyze and model sensor artifacts such as stray light, ghosting, SMILE, and Keystone effects to improve spectral and radiometric purity.
• In-Orbit Cal/Val: Develop and execute Vicarious Calibration frameworks using RadCalNet sites and pseudo-invariant calibration sites (PICS) to monitor sensor stability post-launch.
• Atmospheric Correction: Lead the implementation of advanced atmospheric compensation techniques to deliver analysis-ready Surface Reflectance products.
• SNR Performance Standards: Establish and monitor Signal-to-Noise Ratio (SNR) benchmarks and radiometric uncertainty budgets for every mission.
• Cross-Functional Feedback: Partner with Satellite Hardware teams to influence sensor design (PDR/CDR).

Required Skills

• Deep Domain Expertise: Experience in radiometric calibration of VNIR/SWIR imaging systems, preferably with hyperspectral or multispectral sensors.
• Atmospheric Radiometric Authority: Expert-level command of atmospheric modeling (e.g., MODTRAN, 6SV) and absolute radiometric calibration workflows.
• Mathematical Proficiency: Advanced understanding of detector physics, photonics, and statistical methods for uncertainty quantification.
• Modern Tech Stack: Proficiency in Python (NumPy, SciPy, Pandas) and experience with EO data libraries (GDAL, Rasterio, Spectral).
• Scale Delivery: Experience building automated, cloud-native processing pipelines for petabyte-scale satellite data.

Preferred Skills

• Experience with hyperspectral sensor architectures and multi-detector focal plane arrays.
• Familiarity with international standards such as CEOS/OGC, and experience working with RadCalNet sites or ARD (Analysis Ready Data) compliance requirements.
• Background in developing automated, containerized processing pipelines using Docker and Kubernetes.
• History of conference presentations or peer-reviewed publications in photogrammetry

Candidate Acumen

A strong desire to work in an unstructured, high-growth, fast-paced start-up environment

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