Design, research, test and recommend modern AI training, test and deployment strategies with application to microscope and ultrasound medical images
Benchmark, analyze and improve the performance of existing algorithms, and pre-processing and data augmentation strategies.
Collaborate closely with other engineers to solve interesting and challenging data problems
Turning prototypes of the computer vision algorithms into high quality product ready code
Help establish an effective ML pipeline
Advocate for code and process improvements across your team, and help to define best practices based on personal industry experience and research
Participate in sprint planning, estimation and reviews. Take ownership of deliverables, and work with teammates to ensure high-quality deliverables
Requirements & Skills:
Expert in Machine learning with experience in deep neural networks for computer vision problems, such as image classification and object detection preferably with medical imaging
Strong understanding of Convolutional Neural Networks (CNN), Autoencoders and GANs
Experience in image processing with emphasis on medical images
A Master’s Degree or Ph.D. in Computer Science specializing in image processing, computational photography, computer vision or at least 5 years of experience in the industry or data science competitions
Extensive experience in PyTorch deep learning framework and Python
Familiarity with scientific computing libraries such as numpy, pandas, scikit and image processing libraries such as OpenCV and scikit-image.
Familiarity with Git and Version Control Systems
Experience running accuracy experiments and systematically improving performance
You have strong cross-team communication and collaboration skills
Comfortable being part of a small team of engineers working in an energetic fast paced start-up environment and effective as part of a distributed team
Strong organizational and analytical skills
Excellent written and verbal communication skills
Attention to detail, data accuracy and quality of output
