Company Overview

Plantix is India’s leading digital ecosystem connecting farmers, local retailers and agri-input producers. It is the world’s most downloaded app for farmers - combining artificial intelligence and the expertise of leading research institutions around the globe. Millions of customers use the Plantix Crop Doctor to diagnose crop problems, get recommendations about treatments and the best suited products at their local store.

For the first time in their farming life, many are now able to obtain an accurate diagnosis and the right treatment. On top of this, we provide detailed advice on how to avoid crop loss and to minimize pesticide and fertilizer use. With Plantix, we are able to make a meaningful impact in farmers’ lives.

We have also built the country’s largest digital B2B platform, the Plantix Partner App for agri-inputs - connecting tens of thousand local retailers. The company has over 1000 products listed in the product catalog, offers transparent pricing, easy payment and business management.

Role Description

We are looking for an experienced Senior Geospatial Machine Learning Engineer (f/m/d) to join our team and spearhead the development of a Global Plant Disease Risk Prediction Model. The successful candidate will have a strong background in machine learning and geospatial data analysis, with a proven track record of leveraging these skills to solve complex problems and drive meaningful outcomes.

Responsibilities:

1. Lead the development and implementation of our Global Plant Disease Risk Prediction Model.

2. Collaborate with data scientists, machine learning engineers, and other team members to design and develop cutting-edge machine learning models.

3. Manage the processing and analysis of large geospatial datasets, including remote sensing and field data.

4. Implement and refine machine learning algorithms to improve the accuracy and reliability of our disease risk prediction model.

5. Collaborate with the data collection team to ensure the timely and accurate collection of relevant data.

6. Provide insights and recommendations based on model results to support decision-making processes.

7. Stay updated with the latest advancements in machine learning and geospatial data analysis to continuously improve our model and methodologies.

Key outcomes:

1. Timely delivery of the Global Plant Disease Risk Prediction Model.

2. Improvement in the accuracy and reliability of disease risk predictions over time.

3. Effective collaboration with team members, contributing to a positive and productive work environment.

4. Successful implementation of machine learning algorithms, resulting in improved model performance.

5. Effective management of geospatial data processing and analysis.

6. Regular updates and improvements to the model based on the latest advancements in the field.

7. Positive feedback from stakeholders, including team members, project leaders, and end-users.

Requirements

1. Bachelor's or Master's degree in Computer Science, Data Science, GIS, or a related field.

2. Significant experience in geospatial data analysis and machine learning.

3. Knowledge of machine learning frameworks

4. Familiarity with remote sensing data and related processing techniques.

5. Strong analytical and problem-solving skills.

6. Excellent communication and collaboration skills.

7. Knowledge of agriculture and plant diseases would be a plus.

We encourage individuals who thrive in a collaborative, problem-solving environment, and those who can bring fresh perspectives and experiences to our team, to apply.