Consultant - Data & Model Infrastructure (WFH)

About the job:Key responsibilities:

1. Build and operate ingestion pipelines for public EO data (Sentinel-1/2, Landsat, MODIS, ISRO ResourceSat/Cartosat, Bhuvan) and alternative data signals (weather, IoT, market, mobility, and other non-traditional sources), harmonised into analysis-ready data.

2. Implement and extend the canonical data schema stack STAC 1.1 catalogues, a GeoParquet + pgvector feature store, and validated inference records.

3. Develop, adapt, and fine-tune real-world models from foundation-model embeddings and multi-sensor fusion to now-casting components wired into reliable, testable pipelines.

4. Stand up the supporting infrastructure: data lakes, compute/MLOps workflows, evaluation harnesses, and monitoring.

5. Use AI coding assistants (e.g. Claude Code, Copilot, Cursor) fluently to prototype, refactor, and ship and help set good practices for AI-assisted development.Who can apply:Only those candidates can apply who:have minimum 1 years of experienceare Computer Science Engineering studentsSalary:₹ 3,00,000 - 4,00,000 /yearExperience:1 year(s)Deadline:[hidden]:59:59Skills required:Python, Database Management System (DBMS), DevOps and ClaudeOther Requirements:1. Master's or PhD student in computer science, or a recent graduate of an engineering discipline, with a strong coding and data-modeling background.2. Strong programming (Python essential; SQL a plus) and sound software-engineering fundamentals — version control, testing, clean pipelines.3. Demonstrated fluency with AI coding assistants and a track record of building real things quickly.4. Comfort with data modeling and ML workflows: structuring messy data, fine-tuning models, reasoning about evaluation and uncertainty.About Company:EO-AI Labs is the applied research and commercialisation arm of the Space Technology Accelerator (STAr) at IIT Kanpur. We occupy the space between frontier EO science and the decisions that governments, industries, and communities need to make.

Responsibilities

Key responsibilities:

1. Build and operate ingestion pipelines for public EO data (Sentinel-1/2, Landsat, MODIS, ISRO ResourceSat/Cartosat, Bhuvan) and alternative data signals (weather, IoT, market, mobility, and other non-traditional sources), harmonised into analysis-ready data.

2. Implement and extend the canonical data schema stack STAC 1.1 catalogues, a GeoParquet + pgvector feature store, and validated inference records.

3. Develop, adapt, and fine-tune real-world models from foundation-model embeddings and multi-sensor fusion to now-casting components wired into reliable, testable pipelines.

4. Stand up the supporting infrastructure: data lakes, compute/MLOps workflows, evaluation harnesses, and monitoring.

5. Use AI coding assistants (e.g. Claude Code, Copilot, Cursor) fluently to prototype, refactor, and ship and help set good practices for AI-assisted development.