Design and develop machine learning models to solve business problems.
Work with large datasets, perform data pre-processing, feature engineering and feature selection.
Develop and maintain prototypes, proof-of-concepts and production-level code.
Train, validate and test machine learning models using appropriate techniques and metrics.
Collaborate with cross-functional teams such as data engineers, data scientists and software engineers to build end-to-end solutions.
Keep up-to-date with the latest advancements in the field of machine learning and implement new techniques in ongoing projects.
Deploy machine learning models in a production environment, monitor and maintain their performance.
Troubleshoot and debug complex problems and provide solutions to improve the performance of machine learning models.

Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics or a related field.
Strong knowledge of machine learning algorithms including Random Forest, xGBoost, Clustering etc.
Proficiency in data analysis, data pre-processing, and feature engineering using numpy and pandas.
Knowledge of deep neural networks including, CNNs, RNNs, attention models and transformers.
Provable experience with Python machine learning libraries such as TensorFlow, PyTorch, Scikit-learn, matplotlib, seaborn etc.
Knowledge of cloud computing services like AWS, Google Cloud or Microsoft Azure.
Strong problem-solving skills and the ability to design efficient algorithms.
Excellent communication and collaboration skills, able to work well with cross-functional teams.
Experience with deploying machine learning Models in a production environment using python web frameworks e.g flask, fastapi.

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