Company Overview :

SatSure is a deep-tech decision intelligence company that leverages satellite imagery, remote sensing, and machine learning to provide actionable insights for the agriculture, banking, and infrastructure sectors. By integrating multi-modal data sources, the company enables large-scale monitoring and risk assessment, helping organizations make data-driven decisions in complex environments. SatSure operates at the intersection of space technology and data science, fostering a culture of innovation and technical rigor to solve real-world challenges on a global scale.

Role Overview :

As a Machine Learning Engineer - 2, you will be responsible for building, scaling, and deploying sophisticated models that translate raw satellite data into high-value business intelligence. You will work closely with data scientists, geospatial analysts, and software engineers to bridge the gap between experimental research and production-grade systems. Your contributions will directly influence the accuracy and efficiency of our predictive platforms, ensuring that our clients receive reliable, timely insights that drive critical operational outcomes.

Key Responsibilities :

- Design and implement end-to-end machine learning pipelines to process large-scale geospatial datasets, ensuring high performance and scalability for production environments.

- Optimize deep learning architectures for computer vision tasks, such as image segmentation and object detection, to improve the precision of land-use and crop-monitoring analytics.

- Collaborate with cross-functional teams to integrate model outputs into existing software platforms, enhancing the overall utility of our decision intelligence tools.

- Monitor and maintain model performance in production, proactively identifying drift and implementing retraining strategies to ensure consistent accuracy.

- Automate data preprocessing and feature engineering workflows to reduce manual intervention and accelerate the development cycle for new analytical products.

Required Skillset :

- Demonstrated proficiency in building and deploying machine learning models using Python, with deep expertise in frameworks such as PyTorch or TensorFlow.

- Strong understanding of computer vision techniques and experience working with multi-spectral or satellite imagery data.

- Ability to write clean, maintainable code and manage complex data pipelines using cloud infrastructure like AWS or GCP.

- Strong analytical mindset with the ability to communicate technical findings to non-technical stakeholders effectively.

- A degree in Computer Science, Data Science, or a related quantitative field, reflecting a strong foundation in algorithms and statistical modeling.

- Proven ability to thrive in a collaborative, fast-paced environment, contributing to team goals while maintaining high standards of engineering excellence.