Applied AI Researcher

GalaxEye

Bengaluru

On-site

INR 800,000 - 1,200,000

Full time

14 days+
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Job summary

A leading satellite technology company is seeking an Applied AI Researcher to design and evaluate advanced AI models focused on processing multi-sensor satellite data. Responsibilities include developing models for segmentation, detection, and vision-language tasks, while collaborating with experts to transition prototypes into production. The ideal candidate should have expertise in deep learning, proficiency in Python, and a strong understanding of AI modeling for satellite imagery. This full-time role is suitable for entry-level candidates with a passion for AI research.

Qualifications

  • Hands-on experience developing and deploying foundation models and vision-language models.
  • Experience with preprocessing and data augmentation for geospatial applications.
  • Ability to conduct rigorous experiments and analyze results.

Responsibilities

  • Design, train, and fine-tune models for satellite image processing.
  • Develop models for tasks like detection, segmentation, and vision-language tasks.
  • Publish findings in relevant research forums.

Skills

Expertise in deep learning
Proficient in Python
Experience in machine learning frameworks (e.g., PyTorch)
Knowledge of object detection and segmentation
Collaborative communication skills

Tools

PyTorch
GIS tools

Job description

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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.
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
Seniority level
  • Entry level
Employment type
  • Full‑time
Job function
  • Engineering and Information Technology
Industries
  • Defense and Space Manufacturing

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