JD:
Min 5 years of experience in Machine Learning predictive analytics
5 years of hands on experience in developing models using Machine Learning and Deep Learning related technologies such as Keras Tensor Flow pyTorch GCP AI/ML services.
5 years of experience in Python Spark. Experience working in python libraries like Tensor Flow Spark ML scikitlearn pandas NumPy etc.
Software engineering in Python good with Python SDK able to build libraries and comfortable in deploying Python codes in production.
Hands on experience on Model deployment and Model Monitoring on any public cloud (AWS/Azure/ GCP). GCP experience is an added advantage
Prior experience of handling Supervised Learning Unsupervised learning and Reinforcement learning problems in different industry verticals (Banking/ Finance/ telecom/Retail/ technology etc)
Experience transforming data science prototypes into robust scalable products running seamlessly in production
Experience with implementing CI/CD principles in the Machine Learning domain (ML Ops)
Exposer to containers and its orchestration (Kubernetes).
Google Cloud Platform: Big Query Cloud Composer Vertex AI & AI/ML services in general
Strong hold of concepts in Statistics and expertise in Machine Logs processing text mining and text analytics.
reinforcement learning,software engineering,pandas,machine learning,deep learning,un-supervised learning,statistics,keras,gcp,spark,pytorch,ci/cd principles,ml ops,python,kubernetes,numpy,machine logs processing,containers,model deployment,cloud composer,big query,python sdk,scikit-learn,supervised learning,text mining,google cloud platform,tensor flow,azure,vertex ai,text analytics,gcp ai/ml services,aws,ml,spark ml,tensorflow,model monitoring