Exp - 5-7 yrs
Responsibilities:
Develop, test, and maintain machine learning models and data pipelines.
Automate the training, validation, and deployment of machine learning models in a production environment using tools like MLflow, Airflow & Databricks.
Design and implement model pipelines using tools like Apache Airflow & Kubeflow
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Participate in Agile development activities including sprint planning and code reviews.
Document code and create clear, concise Documentation files for projects.
Use version control systems like Git for code and model management.
Have good handson with github actions and pipelines.
Implement MLOps practices such as continuous integration, continuous delivery, and continuous monitoring for machine learning systems.
Requirements:
Strong programming skills in Python.
Experience with MLOps tools and practices, including MLflow, Apache Airflow, and Databricks.
Experience with Model monitoring and drift detection pipelines.
Good experience with APIs development using FastAPI and having product development mindset.
Experience with machine learning algorithms and statistical models.
Knowledge of time series forecasting is a plus.
Familiarity with Agile development methodologies.
Experience with version control systems like Git.
Familiarity with Jupyter notebooks and Markdown.