Job description (In Detail) :
- Hands on experience in building and deploying production-level data-driven applications and data processing workflows/pipelines and/or implementing machine learning systems at scale in Python and deliver
- Analytics involving all phases like data ingestion, feature engineering, modelling, tuning, evaluating, monitoring, and presenting.
- Focus on building algorithms for the extraction, transformation and loading of large volumes of real time, unstructured data to deploy AI/ML solutions from theoretical data science models
- Proven experience in developing and deploying machine learning solutions using SageMaker, Python, TensorFlow, PyTorch, Scikit-learn, or other frameworks and libraries.
- Solid understanding of machine learning concepts, techniques, and best practices such as data preprocessing, feature engineering, model selection, hyperparameter tuning, validation, testing, challenger models and MLOps.
- Hands on experience in NLP use cases.
- Exposure in Snowflake.
- Exposure in CI/CD tooling.
SKILLS: SageMaker, Python, TensorFlow, PyTorch, Scikit-learn, data preprocessing, feature engineering, model selection, hyperparameter tuning, validation, testing, challenger models, and MLOps, Snowflake, CI/CD
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