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Deepspatial - MLOps Engineer - Data Modeling

Deepspatial - MLOps Engineer - Data Modeling

DeepspatialBangalore
1 day ago
Job description

Description :

Job Role : ML Ops Engineer (Geo AI & ML)

Location : Bangalore

Position Overview :

As an ML Ops Engineer (GeoAI & ML), you will play a key role in designing, developing, and deploying scalable AI / ML models for geospatial applications.

You will bridge the gap between data science and production systems - ensuring that our GeoAI models are efficient, reproducible, and seamlessly integrated into operational workflows.

This position requires a unique blend of geospatial expertise, machine learning proficiency, and DevOps / ML Ops practices.

You will collaborate with researchers, data scientists, and engineers to advance cutting-edge solutions in areas such as remote sensing analytics, environmental monitoring, urban intelligence, and location-based insights.

Key Responsibilities :

Geospatial Expertise :

  • Proficiency with ArcGIS, QGIS, or similar GIS platforms
  • Experience with Google Earth Engine (GEE), remote sensing, and satellite image processing
  • Strong understanding of spatial analysis, geostatistics, and geospatial data visualization

AI / ML & Programming :

  • Advanced Python programming skills (scikit-learn, TensorFlow, PyTorch, etc.)
  • Proficiency in R for statistical analysis and visualization
  • Experience with SPSS for data modeling and statistical interpretation (preferred)
  • Mandatory Requirement :

  • At least one international publication in a reputed journal indexed in Scopus or Web of Science
  • Qualifications :

  • B. / B.Tech with M.Tech / Ph.D specializing in GeoAI, Machine Learning, or related fields OR
  • MCA / MBA with a strong specialization or practical experience in GeoAI & ML
  • Desirable Skills :

  • Hands-on experience with cloud platforms such as AWS or Azure
  • Familiarity with ML Ops, CI / CD pipelines, and model deployment workflows
  • Exposure to satellite imagery, LIDAR data processing, and PostGIS
  • Strong understanding of data versioning, automation, and model lifecycle management
  • Why Join Us ?

  • Work on real-world geospatial AI challenges with social and environmental impact
  • Collaborate with a multidisciplinary R&D team of data scientists, engineers, and geospatial experts
  • Opportunities for research publications, international collaborations, and career growth
  • (ref : hirist.tech)

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