Data Science Engineer (IRC229898) (offline)

Alcon is continuously advancing their medical devices and further enabling them with connectivity features and cloud based services. Still adoption of new generation solutions is happening gradually and in the field it is common to have a mix of legacy and new solutions within one setup.

This project involves developing, training and testing AI/ML algorithm for surgical automation and generating functional modules to demonstrate the real-world clinical usage of the AI/ML algorithm.

Job Description

1. mathematics: linear algebra, calculus, theories of probability
2. Machine learning: model training, evaluation, hyperparameter tuning
3. Data science and MLOps experience
4. CV background: OpenCV, PIL or scikit-image
5. Pytorch experience
6. Strong C++ programming

Job Responsibilities

Task #1: Surgical video data annotation pipeline and quality-check. This task involves working with a 3 rd party vendor to enabled a streamlined process to conduct data annotation quality check and to ensure unbiased outcome from the annotation process for AI/ML algorithm development. In particular, the subtasks are,

 Extract eye images from video data of cataract surgery and provide the collated data to 3rd party annotator for annotation.
 Conduct quality check on the annotation data received from 3 rd party vendor, archive the data files, and convert them into the right data format for algorithm training.

Task #2: Serve as resource augmentation to train and fine-tune predefined deep learning models using the annotate dataset, as and if requested by the Alcon Med Data Science team

Task #3: Provide concrete technical support to help deploy AI algorithm on edge device. This task may involve, but not limited to, (i) providing guidance on the technical solution and the correct edge-device option for this project and (ii) debugging any potential technical issues while deploying prototype AI/ML algorithm to edge-device.