Job Overview
            
                
                
                
                    Category
                    Computer Occupations
                 
                
             
            
            
         
        
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            Job Description
            
                GalaxEye is building groundbreaking AI-first products that transform satellite data into actionable intelligence.
We’re creating the world’s most advanced multi-sensor geospatial intelligence platform, fusing data from space, AI, and high performance computing.
Join us as we engineer the digital backbone of this vision.
We're seeking a Sr. Backend Engineer to bridge the gap between our AI/CV algorithm teams and Satellite Intelligence Platform.
You’ll play a key role in building the infrastructure that takes cutting-edge computer vision models from research to production — designing workflows, packaging modules, and orchestrating them on GPU clusters.
Key Responsibilities
- Collaborate with AI/CV teams to define interfaces and packaging standards for algorithms.
- Optimize the algorithm's performance and implementation for deployment (On GPU Cluster)
- Develop Python workflow scripts to link multiple algorithm modules into an orchestrated job pipeline.
- Dockerize and integrate algorithms with a Slurm-based workflow orchestrator for distributed execution.
- Test, validate, and benchmark algorithms before production rollout.
- Establish DevOps hygiene and maintain CI/CD pipelines across AI/CV and platform teams.
- Handle versioning, tagging, and publishing of algorithm packages with proper documentation and release notes.
Required Skills
- Solid in Python scripting, and scientific computing frameworks like Pytorch, Numpy, OpenCV, Scipy etc.
- Solid foundation in mathematics and capability to understand and optimize computing logic
- Experience with Docker, CI/CD (GitHub Actions, GitLab, Jenkins).
- Familiarity with Slurm, GPU clusters, and workflow orchestration.
- Exposure to AI/ML model packaging, Python environments (Conda, PyPI), and cloud/on-prem infra.
            
         
  
  
  
        
        
        
        
        
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