Design and implement cloud solutions and setup MLOps on cloud (GCP).
Implement and track best practices for model development and deployment life cycle.
Data science models testing, validation and automation of test cases.
Collaborate with a team of data scientists, data engineers and solution architects.
2-4 years of industry experience with 1+ years of hands-on AI or ML system development experience.
Highly skilled in python with a good understanding of dockers and containers.
Experience in model deployment, model monitoring, and model refresh experience in any orchestration tool like MLflow and Kubeflow is expected.
Expertise in design and development of ML-based solutions.
A decent understanding of data science techniques.
Decent experience in developing deep learning models using frameworks like Tensorflow, Keras, Caffe and PyTorch.
Good experience working with data pipelines and ETL/ELT.
Comfortable in conversational English.
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