Job highlights

- This internship offers an opportunity to work on proprietary datasets and contribute to novel research problems at the intersection of computer vision,multimodal AI,and remote sensing.

What Youll Work

On . SAR-to-EO image translation using generative models such as diffusion models and GANs

- . Good to Have .

- Experience with EO,SAR,or geospatial datasets

Our AI team builds cutting-edge deep learning systems that extract intelligence from high-resolution EO and SAR satellite data. This internship offers an prospect to work on proprietary datasets and contribute to novel research problems at the intersection of computer vision, multimodal AI, and remote sensing.

What Youll Work On

- SAR-to-EO image translation using generative models such as diffusion models and GANs.

- Vision-Language Models (VLMs) for understanding, retrieval, reasoning, and interaction with EO and SAR imagery.

- Foundation models for remote sensing, including representation learning, multimodal fusion, segmentation, detection, and large-scale pretraining on satellite imagery.

This is a research-focused role where you'll be expected to read deeply, experiment rigorously, and contribute novel ideas rather than simply implement existing solutions.

What Youll Do

- Conduct structured literature surveys on state-of-the-art deep learning, multimodal learning, and remote sensing research.

- Reproduce and benchmark recent research papers on EO and SAR datasets.

- Train, fine-tune, and evaluate deep learning models on proprietary high-resolution satellite imagery.

- Design and execute rigorous experiments with proper tracking,



ablations, and analysis.

- Develop and adapt architectures including CNNs, Vision Transformers, diffusion models, GANs, and multimodal foundation models.

- Analyze model performance, identify failure modes, and propose improvements.

- Collaborate closely with researchers and engineers, present findings, and contribute to technical reports and research publications.

Requirements

- Strong Python and PyTorch.

- Solid foundations in deep learning and modern computer vision.

- Experience with one or more of the following:

- - Transformers and Vision Transformers.

- Generative models (Diffusion Models, GANs, VAEs).

- Vision-Language Models or multimodal learning.

- Familiarity with Linux, Git, and GPU-based training workflows.

- Strong experimental and research mindset.

Good to Have

- Experience with EO, SAR, or geospatial datasets.

- Familiarity with Sentinel-1, Sentinel-2, Landsat, SpaceNet, BigEarthNet, SEN12MS, or related datasets.

- Experience with CLIP, BLIP, LLaVA, SigLIP, Qwen-VL, or similar multimodal models.

- Exposure to raster geospatial data tools such as GDAL or rasterio.

- Experience with experiment tracking tools such as MLflow or Weights & Biases.

- Publications, research projects, or open-source contributions in computer vision, generative AI, multimodal AI, or remote sensing.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AI Research Intern - DIL (Bengaluru)
🏢 GalaxEye Space
📍 Bengaluru