Hummingbird Technologies is the leading global remote sensing business for agriculture, using artificial intelligence and imagery analytics gathered from drones, planes and satellites technology, combined with weather and soil data and expert plant pathology to enable precision agriculture. We use the most advanced machine learning and computer vision techniques, delivering actionable insights on crop health directly to the field meaning farmers on the ground are able to manage their land in a more sustainable manner.
We were awarded KPMGs Best British Tech Startup 2019 and Cognition X Best AI Product for Agriculture 2018.
Hummingbird was founded in 2016 at the Imperial College technology incubator and we have raised over $20m in funding so far. Existing backers of the business include: Horizons Ventures, European Space Agency, Sir James Dyson, TELUS, BASF, and SALIC. We also have tech partners which include Google UK and Cranfield University.
We are 65 people and operate internationally with offices in the UK, Ukraine, Russia, Australia, Brazil and Canada.
Summary of Role
You will join a talented team of machine learning researchers, big data scientists, computer vision experts, and software engineers. You will be expected to get up to speed rapidly in this fast-paced, multi-disciplinary environment. We are not solving trivial problems, but researching and developing to shape the future of crop and farm management through the creation of predictive analysis products which will be used across the globe to feed the world and minimise the long-term environmental impact of modern, large-scale agriculture and help us become a leader in carbon capture measurement in agriculture.
Your main responsibility will be to help develop machine learning algorithms to create cutting edge services for agriculture.
- MSc or Phd in Computer Science, Machine Learning, Remote Sensing, Statistics or any related field
- Experience creating, building and shipping models to users
- Breath of knowledge of Machine Learning methods and algorithms, namely neural networks, time-series, classification / regression and others
- Experience with typical Machine Learning stack and tools: Python, TensorFlow / PyTorch / Keras, Jupyter, Pandas / SciPy / scikit-learn
- Strong expertise in remote sensing and image processing
- Shows interest in managing and leadership
- Experience working with satellite and/or UAV imagery
- Experience with geospatial data processing and analysis tools like GDAL, QGIS, ArcGIS
- Experience with image processing tools and libraries such as OpenCV, scikit-image, matplotlib, etc.
- Educational or work exposure to agriculture, remote sensing, soil sciences or similar fields
- Experience working in a startup environment
- Experience working in agritech sector
- Private Healthcare
- Flexible working
- Cycle to work scheme
- Learning & development budget
- Government Pension scheme
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