Geospatial Machine Learning Engineer
Alt Carbon2+ yrsBengaluruOn-siteDirect career pageEst. 12–22 LPA
Posted 1d ago
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Job description
Structured overview of role & requirements
About This Role
- Build scalable data pipelines for diverse geospatial datasets from public and proprietary sources.
- Collaborate with data scientists and experts to productionize and manage multi-modal ML models, including tracking and registry.
- Optimize and deploy ML models at scale on cloud/on-premises, implement monitoring for data and model drift with alerting.
Minimum Requirements
- >2 years experience as Data Engineer or ML Engineer.
- B.Tech or M.Tech in Machine Learning, Data Science, Computer Science, Geoinformatics, or related fields.
- Hands-on experience processing geospatial data (Sentinel, Landsat, MODIS, ERA5) and formats (GeoTIFF, NetCDF, ESRI Shape).
- Proficient in Python with experience in ML/DL frameworks (PyTorch, scikit-learn, XGBoost, LightGBM) and deploying models on AWS (Sagemaker, S3, EC2).
Ideal Candidate Profile
- Experienced in building and managing end-to-end ML pipelines with geospatial focus and multi-modal data fusion.
- Comfortable working closely with cross-functional teams including data scientists and domain experts for model hardening and deployment.
- Skilled in ML lifecycle tools like MLflow and workflow orchestration tools such as Airflow, with familiarity in cloud-native geospatial technologies.