Python Backend Engineer (Remote)

Do you enjoy writing clean, reliable Python code that drives complex systems behind the scenes?

Are you motivated by the idea of building software that supports climate and environmental solutions?

We are looking for a Python Backend Engineer who can take scientific and modelling concepts and turn them into robust, production-ready systems.

You will help develop and maintain the backend of a sophisticated modelling framework that combines real world data with predictive tools to understand soil carbon and agricultural systems.

This is a hands on role in a small team where the work is meaningful, the tech is modern, and your contributions will have real impact from day one.

What you will be doing

• Designing and maintaining backend systems for data driven environmental modelling
• Building out Python services that integrate crop growth, soil carbon, water, and nitrogen models
• Implementing Bayesian inference workflows and supporting ensemble model pipelines
• Writing data ingestion and processing code to work with large scientific datasets
• Building validation and testing tools to ensure model performance and reliability
• Supporting machine learning integrations for improved model prediction
• Collaborating with scientists and other engineers to translate research into working code
• Writing clear documentation and communicating technical work to a range of users

What we are looking for

• Strong Python development skills, including experience with libraries like NumPy, SciPy, pandas, and scikit learn
• Experience building backend systems for data science or scientific applications
• Familiarity with Bayesian frameworks such as PyMC or similar tools
• Comfortable working with APIs, containers, and CI workflows
• Experience with software engineering best practices such as testing, version control, and documentation
• A degree in computer science, data science, engineering or a related technical field

Nice to have

• Experience working with environmental or scientific models
• Exposure to satellite or geospatial data and tools like GeoPandas
• Familiarity with cloud infrastructure like AWS, Azure, or GCP
• Experience using Docker or other container tools
• Interest in or experience with agricultural systems or climate related data
• Contribution to scientific research or technical publications