Job vacancy: Software Developer
Location: Office-based in Bicester, UK, with flexible home working
Benefits: Pension, 28 days holiday, modern working environment, great team spirit
Reports to: Senior AI Developer
Are you an experienced Python developer? Come and work for the UK’s top Tech Innovator as we develop machine-learning solutions to one of the world’s most pressing problems – water scarcity.
Our pioneering AI detects underground water leaks and works out their size through super accurate analysis of acoustic data.
You’ll be an integral part of FIDO AI’s ongoing world-beating development, working as part of a Scrum team focused on delivering machine learning solutions.
Although largely based at our Bicester office, there are options for remote and flexible working. We’re a small but enthusiastic team working in a great modern environment with good benefits.
Please note that the role will be largely office-based and candidates will be asked to demonstrate their proficiency in Python by taking a 90-minute online test.
No agencies please.
- Develop a wide range of Python projects to assist the AI team in building models, datasets, and ML architecture
- Writing unit tests and testing Python codebase
- System and integration testing of FIDO products
- Development of tools to assist with building and cleaning datasets
- Deployment and delivery of machine learning models and predictions
- Contribute to maintaining and building robust cloud-based systems
Skills and experience
- BSc/BEng degree in Software Engineering, Computer Science or similar.
- Python expert. Candidates will be asked to demonstrate proficiency through an online screening test
- 2+ years of commercial experience programming in Python
- Experience building web or application-based Python programs (Django, Tkinter, Flask)
- Experience in unit and integration testing
- Proficiency with graph databases, SQL, Linux, and cloud-based architectures would be beneficial
- Agile Scrum experience preferred
- Awareness of software development, ML Ops and Dev Ops best practices