Mission Design Intern
Work with the brightest minds, including ex-ISRO scientists and global space industry experts, at one of the select few companies in the country pioneering cutting edge EO payloads.
We’re hiring an Image Processing Intern who is passionate about developing algorithms to make raw satellite imagery clearer, cleaner, and more usable. The ideal candidate will be eager to design and test methods for statistical normalization, contrast enhancement, and pixel-level transformations—unlocking meaningful insights from complex, multi-band image data.
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 focus on building next-gen payloads tailored for industry-specific applications.
Our high-resolution, optical, multispectral payloads, equipped with edge computing and wide coverage capabilities, maximize the value generated from every pixel of satellite imagery.
Rooted in SatSure’s legacy of delivering last-mile applications across sectors like Utilities, Aviation, Agriculture, BFSI and Climate Action, KaleidEO offers modular solutions for the entire EO value chain spanning payload development, launch, mission operations, and data analytics
At KaleidEO, we are committed to shaping the future of Earth Observation and putting Indian space tech on a global map, and we invite you to be part of this exciting journey.
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.
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Apply mathematical tools like:
• Matrix operations and eigenanalysis for image transformations
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.