Junior data Scientist

Responsibilities:

• Understand and elaborate the use case
• Research and review academic papers related to the use case
• Create blueprints, solution architecture using machine learning models, design the solution and create the code base to train, test and evaluate the models
• Create inference modules for the ready models; create endpoints and APIs to use the inference function of the machine learning models; train the models in local and/or cloud environments such as AWS, Azure and GCP
• Deploy the models and APIs to cloud or edge devices

• Bachelor’s degree, but desirable master’s degree in engineering fields (computer science), mathematics or physics
• At least 2 years of experience with Python and 1 year professional experience with PyTorch, TensorFlow, Keras and Scikit.
• Understanding of deep learning and computer vision solutions such as classification, deep metric learning, object detection, semantic segmentation and instance segmentation
• Has worked on backend development for creating APIs, has an experience in the work on any of cloud providers such as AWS, Azure or GCP to train, deploy and run deep learning models, has worked with containerization
• Team player, has worked with Agile and has knowledge on project management
• Fluent in English

• Worked in the preparation of production level deep learning models for computer vision solutions
• Developed solutions using deep learning models that can work both with CPU and/or GPU
• In-depth understanding of software architecture and cloud architecture
• Having computer vision solutions using deep learning (developed from scratch) in GitHub is a big plus