Key responsibilities:
- Conduct data discovery and exploratory analysis on open-source Earth observation datasets.
- Collaborate with researchers and engineers to design experiments, share insights, and iterate on approaches while writing clean, maintainable code.
- Build and train machine learning models across multiple data modalities (RGB, multispectral, radar, LiDAR, text, etc.).
- Benchmark models against state-of-the-art baselines from peer-reviewed research.
- Maintain experiment logs, ensure reproducibility, and contribute to shared code repositories
- Document methodologies and share results through technical reports, internal presentations, or research publications.
What we are looking for:
- Pursuing (or recently completed) B.Tech, M.Tech, MS (Research), or PhD in a technical field relevant to the role (e.g., CS, EE, EC, AI, etc.),
- Proficiency in Python, with experience in ML/DL frameworks (PyTorch)
- Prior hands-on experience with ML/DL projects (academic, research, or personal) in topics related to computer vision
- Skilled at translating research papers into working prototypes and practical implementations.
Good to have:
- Prior experience in working with geospatial data and familiarity with geospatial processing libraries (GDAL, rasterio, geopandas, xarray, rioxarray)
- Publications in remote sensing or ML/vision conferences.
