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Location: Nashik, Maharashtra

Experience: 3–4 Years

CTC: ₹6 LPA – ₹8 LPA (depending on skills, experience, and project ownership)

Company: Rotten Grapes Private Limited

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About Rotten Grapes Private Limited

Rotten Grapes Private Limited is a geospatial-first software development company specializing in GIS, Earth Observation, and applied Artificial Intelligence. We design and build production-grade platforms and decision-support systems for clients across forestry, agriculture, climate, water resources, urban planning, and infrastructure domains.

Our work focuses on converting research and experimental models into scalable, real-world systems, primarily using open-source technologies. We work with government bodies, international organizations, and private enterprises globally, helping them operationalize satellite data, spatial analytics, and AI-driven insights while significantly reducing long-term platform costs.

Role Overview

We are hiring a Machine Learning Engineer with 3–4 years of hands-on experience to join our AI and Geospatial R&D team at our Nashik office.

This role is suited for engineers who enjoy working with complex real-world datasets, understand the difference between academic ML and production ML, and are comfortable owning models from experimentation to deployment.

You will collaborate closely with GIS engineers, remote sensing experts, and backend teams to design, build, optimize, and integrate ML models into operational platforms used by real clients.

Key Responsibilities

• Develop, train, and evaluate machine learning and deep learning models for geospatial and Earth Observation use cases
• Work with satellite imagery, raster and vector data, and spatio-temporal datasets
• Build and maintain end-to-end ML pipelines including preprocessing, training, inference, and validation
• Optimize models for performance, scalability, and production readiness
• Collaborate with GIS and backend engineers to integrate ML models into APIs and web platforms
• Translate research papers and proof-of-concept models into stable, maintainable production systems
• Participate in model benchmarking, documentation, and technical decision-making
• Contribute to ongoing R&D initiatives and experimentation