The Role
Design, train, fine-tune, and evaluate foundation models and vision-language models for multi-sensor satellite imagery. Develop detection, segmentation, change detection, retrieval, captioning, and visual question-answering systems. Build scalable geospatial data pipelines, conduct rigorous experiments, publish research, and collaborate with engineering, MLOps, product, and domain teams to transition prototypes into production.
Summary Generated by Built In
Job Description
Requirements
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.
- 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.
Skills Required
- Expertise in deep learning, computer vision, and machine learning, including developing and deploying foundation models and vision-language models
- Proficiency in Python and machine learning frameworks such as PyTorch
- Experience with large-scale image and multimodal datasets, including preprocessing and data augmentation for geospatial applications
- Understanding of object detection, segmentation, metric learning, and vision-language integration in remote sensing
- Familiarity with or strong interest in satellite data modalities including SAR, multispectral, and hyperspectral data
- Ability to conduct rigorous experiments and analyze results to guide iterative improvements
- Collaborative communication skills and ability to work in interdisciplinary teams
- Experience building or fine-tuning vision-language models or foundation models for satellite or aerial imagery
- Exposure to geospatial data standards such as GeoTIFF and NetCDF, and GIS tools
- Familiarity with model optimization for efficient cloud or edge deployment
- Publications or open-source contributions in AI, vision-language, or remote sensing research
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The Company
What We Do
GalaxEye is an Indian space-tech startup developing advanced Earth-observation technologies. Its flagship Drishti Mission uses a multisensor imaging satellite combining optical and Synthetic Aperture Radar data to produce high-resolution imagery, including through cloud cover and at night. The company applies artificial intelligence, computer vision, and geospatial analysis to support governments, defense organizations, and industries with actionable insights.
