Deepspatial - MLOps Engineer - Data Modeling

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