Your primary focus is to interpret real world use cases that can be solved by AI/ML/DL and create new pipelines in terms of the overall solution. Do research and present your findings with respect to the problem and propose the best solution or use available AI APIs, open-source and state of the art research when needed.
Main duties and responsibilities:
● Translate real-world problems into components solvable by ML and DL techniques.
● Train or build new models that can be applied to practical problems.
● Build or source the necessary datasets for training and fine-tuning AI/ML/DL models.
● Analyze model performance and formulate necessary recommendations.
● Present thoughts and ideas in an organized manner and use Jupyter Notebooks in whatever platform.
● Graduate of any 4 or 5 year course related to software development, information systems, and analysis, e.g. Statistics, Math, Computer Science, Information Technology, Computer Engineering, or equivalent.
● Basic knowledge in APIs, containers, and clustered systems.
● At least 1 year of commercial experience in using software libraries and toolkits for high-performance numerical computation such as Scikit*, NLTK, Caffe/2, PyTorch/Torch and Tensorflow.
● At least 1 year of commercial experience in Python.
● Knowledge in Machine Learning and Deep Learning algorithms, specifically NLP, is a plus.
● Knowledge in any MLOps tools is a plus.
● Readiness to dive in and become part of a winning team.
● Strong analytical and implementation skills.
● Excellent English reading and writing skills is a plus.
● Responsible and can work with minimum supervision.
● Ability to work under pressure.