Image Processing Intern

We’re hiring an Image Processing Intern who is passionate about solving real-world problems using cutting-edge satellite data, particularly in the domain of multispectral high-resolution imagery.

About KaleidEO

KaleidEO, a subsidiary of SatSure, is an upstream leader in Earth Observation, building a full-stack company from India. As an 'analytics-first' payload innovator, we specialize in building next-gen, high-resolution, multispectral payloads with edge computing and wide coverage capabilities.

Rooted in SatSure’s legacy of building applications across sectors like Utilities, Agriculture, Aviation, BFSI, and Climate Action, we also provide end-to-end EO solutions, from payload development and launch to mission operations and data analytics.

At KaleidEO, we are shaping the future of Earth Observation and putting Indian space tech on the global map. If you thrive on challenges and are passionate about pushing the boundaries of image processing, this is your calling!

Roles and responsibilities

• To write algorithms that make raw images clearer, cleaner, and more usable, from denoising and sharpening to balancing color channels across spectral bands.
• Dive into multi-band image data to explore spatial and spectral relationships.
• Design and test methods for statistical normalization, contrast enhancement, and pixel-level transformation.

• Apply mathematical tools like:

• Matrix operations and eigenanalysis for image transformations
• Fourier and wavelet transforms for signal decomposition and enhancement
• Probability models to analyze and correct noise or distortion

• Explore quality metrics like MTF, entropy, SNR, and even design your own custom metrics.
• Visualize insights and performance in clean, interpretable formats using Python-based tools.
• Collaborate with a technically strong team while keeping your thinking original and your code elegant.

Qualifications:

• Currently pursuing a Bachelor’s degree in Engineering, Physics, Computer Science, Mathematics, or any field that taught you to think rigorously.
• Comfortable with mathematics as a toolkit — especially linear algebra, calculus, basic optimization, and probability/statistics.
• Prior experience (project, course, or hobby) using Python to process, analyze, or visualize image or signal data.
• Ability to write clean, modular code and a willingness to debug methodically.
• A mindset that’s scientific, curious, and not afraid to get your hands dirty with raw data.
• Understanding of image/signal processing.

Good to Have

• Experience with image processing libraries like OpenCV, scikit-image, PIL, or MATLAB equivalents.
• Exposure to signal processing concepts, filters, convolutions, frequency-domain analysis.
• Understanding of multi-dimensional arrays and techniques like PCA or band decorrelation.
• Comfort with performance optimization in Python (e.g., vectorization, profiling, or multithreading).
• Experience using Git or version control for code organization and collaboration
• A personal or academic project where you explore patterns, noise, or structure in visual or sensor data.

What You’ll Take Away:

• A solid understanding of how to move from raw pixels to analytical-ready data.
• Firsthand experience building scalable, modular algorithms that deal with real-world complexity.
• Insight into how mathematics powers imaging pipelines used in domains like Earth observation, scientific computing, high performance computing and AI.
• A chance to collaborate, experiment, and contribute to something meaningful.