AI Researcher

GALAXEYE SPACE SOLUTIONS PRIVATE LIMITED; Bengaluru Urban; On-site; INR 900,000 - 1,400,000; Full time

Job summary

GalaxEye Space Solutions Private Limited in Bangalore North, India, is seeking an Applied AI Researcher to design, build, and evaluate advanced ML models, focusing on foundation models and VLMs for multi-sensor satellite data.

You will prototype architectures, create scalable data pipelines, collaborate with product and domain experts, and contribute to research publications and production handoffs.

Qualifications

• Expertise in deep learning, computer vision, and ML with foundation models and VLMs.
• Proficiency in Python and ML frameworks, especially PyTorch.
• Experience with large-scale multi-modal datasets and geospatial data.
• Understanding of object detection, segmentation, and cross-modal reasoning.
• Interest in satellite data modalities (SAR, multispectral) and AI modeling.

Responsibilities

• Design, train, and fine-tune foundation models and VLMs for satellite data.
• Develop models for detection, segmentation, change detection, retrieval, and VLM tasks.
• Prototype architectures and training methods for robust remote sensing AI.
• Create scalable pipelines for large geospatial datasets and benchmarking.
• Collaborate with AI engineering, product, and domain experts to translate needs into deliverables.
• Support transition of research prototypes to production with MLOps teams.
• Publish findings and represent GalaxEye in AI and remote sensing forums.

Skills

Deep learning

Computer vision

Foundation models

Vision-language models

Satellite imagery

PyTorch

Python

Geospatial data

MLOps

Research

Tools

PyTorch

Python

GeoTIFF

NetCDF

GIS tools

Job description

GALAXEYE SPACE SOLUTIONS PRIVATE LIMITED | Full time

AI Researcher

Bangalore North, India | Posted on 02/25/2026

GalaxEye seeks an Applied AI Researcher to design, build, and evaluate advanced machine learning models, focusing on foundation models and vision-language models (VLMs) tailored for multi-sensor satellite data. This role bridges research innovation and practical deployment, unlocking intelligence from satellite imagery through state-of-the-art AI techniques.

Key Responsibilities

• Design, train, and fine-tune foundation models and VLMs specifically adapted to satellite and geospatial image processing, enabling better semantic understanding and cross-modal reasoning.
• Develop models for detection, segmentation, change detection, retrieval, and vision-language tasks like image captioning and visual question answering on satellite imagery.
• Prototype and experiment with novel architectures and training methods to improve model accuracy, robustness, and efficiency in remote sensing environments.
• Create scalable data processing and experimentation pipelines for large geospatial datasets, ensuring reproducibility and rigorous benchmarking.
• Collaborate with AI engineering, product, and domain experts to translate mission needs into research deliverables and practical AI solutions.
• Support transition of research prototypes to production via close collaboration with MLOps and software teams.
• Publish findings in AI, computer vision, and remote sensing forums; represent GalaxEye in the global research community.

Requirements

Required Qualifications

• Expertise in deep learning, computer vision, and machine learning with hands-on experience developing and deploying foundation models and vision-language models (VLMs).
  

• Proficiency in Python and ML frameworks such as PyTorch, with specialties in model fine-tuning for specialized domains like satellite imagery.
  

• Experience with large-scale image and multi-modal datasets, including preprocessing and data augmentation for geospatial applications.
  

• Solid understanding of object detection, segmentation, metric learning, and vision-language integration in remote sensing contexts.
  

• Familiarity or strong interest in satellite data modalities (SAR, multispectral, hyperspectral) and their implications for AI modeling.
  

• Demonstrable ability to conduct rigorous experiments and analyze results to guide iterative improvements.
  

• Collaborative communication skills and the ability to work in interdisciplinary teams.

Preferred Qualifications

• Prior experience building or fine-tuning VLMs or foundation models for complex imaging domains such as satellite or aerial imagery.
  

• Exposure to geospatial data standards (GeoTIFF, NetCDF) and GIS tools.
  

• Familiarity with model optimization techniques to enable efficient deployment on cloud or edge platforms.
  

• Publications or open-source contributions in AI, vision-language, or remote sensing research.