Lead Computer Vision Engineer
- Data Science
About the role
Lead Computer Vision Engineer – Aggritech startup – London (flexible working) £120k
Fancy saving the planet with your Computer Vision powers?
We’re looking for a Lead Computer Vision Engineer to join us to develop Computer Vision tools for the agricultural sector.
We’re a seed funded start-up that have been around just over 3 years, we’re working in a pretty unique space and solving a complex real world problem for farmers and, by default, most people.
What will I do?
You’d be leading a team developing Computer Vision products using Deep Learning methods and state-of-the-arts in Computer Vision, from research through to deployment. You’ll have a team of ML Engineers to help you but will be hands on and oversee data collection, storage and processing.
What must I have done?
We’d like you to have spent at least 3 years applying research in industry, with a background in academic research which would include a PhD/MSc in a Machine/Deep Learning/Computer Vison related subject.
You’d have experience with the following:
- Deep Learning frameworks – (Tensorflow, PyTorch, Neural Networks)
- Real time object detection – (Faster-RCNN, YOLO, Single shot detection (SSD) EfficientNet)
- Computer Vision Libraries (we use OpenCV)
- Python libraries (NumPy, SciPy, SKLearn etc)
- Experience managing/mentoring small teams
What will I receive?
Along with a competitive salary, being a startup you will receive:
- Equity in the company – Joining early on means you get a bigger share in the company.
- An extremely flexible working policy
- 30 days holiday
- Plenty of learning and development
I’d like to find out more
Great, if you feel this is the role for you or would like to find out more get in touch by clicking the ‘apply now’ button or get in touch with me by the following:
- Email me at email@example.com
- Call me on 01412250189
Please note: you must be in the UK to be considered for this role and we are unable to consider applications from students with solely academic experience.