Machine Learning Engineer - Python Programming

Role : Lead Machine Learning Engineer

- Lead the development of machine learning components for their innovative MRV and decarbonization platform.

- This role will be crucial in integrating advanced AI, satellite remote sensing, and comprehensive carbon footprint tracking to provide a holistic solution for agricultural enterprises, government agencies, and farmers.

- Development of AI-driven systems for visualizing and managing Scope 3 Category 1 emissions for large agricultural enterprises

- Creation of machine learning models like crop classification, yield estimation, soil health analysis using satellite data

- Implementation of advanced analytics and machine learning models for carbon/ GHG emission prediction and reduction recommendations

- Integration of data from various sources including satellite imagery, IoT devices, local soil analysis facilities, Climate data sources.

Skills/Criteria (Mandatory & Optional) :

- Minimum of 4 years of work experience as a Machine Learning Engineer or Data Scientist, with atleast 2 years of experience in data modeling(Crop classification or Soil moisture estimation or Carbon sequestration modeling)

- Should have strong deep learning projects in the candidates portfolio.

- Strong proficiency in Python and experience with cloud platforms (AWS). Extensive experience with machine learning frameworks and data processing technologies

- Experience with satellite ( Active / Passive - S1, S2, Landsat, Modis etc.) Image processing and geospatial datanalysis

- Knowledge of carbon accounting principles and environmental reporting standards

- Experience tech leading cross-team engineering efforts Strong software engineering practices including debugging/profiling, version control, and system design

- Excellent problem-solving skills and ability to work in a fast-paced, innovative environment

- Experience with or understanding of satellite-based remote sensing and crops, agriculture Knowledge of microservices architecture and experience with database systems (RDBMS/NoSQL)

Languages : Python, TypeScript

Machine Learning : TensorFlow, Keras, PyTorch

Models : CNN, LSTM, Transformers, Vision Transformers

Cloud : AWS (EC2, EKS, S3, SageMaker, etc.)

Version Control : Git, GitHub

Project Management : JIRA Communication

Tools : Slack, Notion