Algorithms, AWS, Bash scripting, C Programming, C++, Computer Vision (CV), Docker, Git, Jenkins, Keras software library, OpenCV, Python Programming, Signal processing, TensorFlow
Role
The focus of this role is to augment existing Computer Vision frameworks. We're looking for candidates with good experience in deep learning, cloud deployment, and a passion for well-engineered software. The candidate must love Test Driven Development, and possess an in-depth knowledge of Python. Previous experience in using Computer Vision for digital health purposes is a great benefit.
Responsibilities
As a Senior Computer Vision Engineer, you will be responsible for building fully automated vision systems as well as cloud deployment. You will also work with our team to bring new features to the existing vision solution, programming principally in Python.
As part of our engineering team, you will also work with other engineers and data scientists, giving you the opportunity to learn new skills. Your contribution will be towards a pipeline of our products that will make surgery safer.
What we are looking for?
We are looking for a Senior Computer Vision Engineer with strong experience in Deep learning to drive the deployment and improvement of cutting-edge surgical vision systems. You will be part of a collaborative and growing team of vision engineers and data scientists based in our central London office. Our team also comprises Software Engineers and Machine Learning scientists who are building cutting-edge algorithms for safer surgery. Open-minded, entrepreneurial candidates who intend to use their skills to enhance global health are the ideal candidates.
Eligibility
Essential Criteria
M.Sc. or Ph.D. in Computer Vision, Signal Processing, Engineering, or Applied Sciences. Candidates are required to have 3+ years of professional experience.
Desirable Skills
Benefits
We at Scalpel are making surgery safer, smarter, and greener. We use AI & advanced computer vision to build a surgical intelligence platform that enables peri-operative teams to make augmented and data-driven decisions in the Operating Room and beyond.