Job Summary
Experience in designing & implementing solution in mentioned areas:
Strong experience in developing AI/ML models on Google Cloud Platform Core Skills : TensorFlow, Recommendation Systems, Deep Learning, NumPy, Pandas, Sklearn, Python, R, Keras, Statistical Analysis, Computer Vision, PySpark
Key Responsibilities
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, TensorFlow, pyTorch, GCP AI/ML services.
• 5+ years of experience in Python, Spark. Experience working in python libraries like TensorFlow, Spark ML, scikit-learn, 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, Un-supervised 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: BigQuery, 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.
Skill Requirements
Technical / Functional Skills:- Experience in designing & implementing solution in mentioned areas:
Strong experience in developing AI/ML models on Google Cloud Platform Core Skills : TensorFlow, Recommendation Systems, Deep Learning, NumPy, Pandas, Sklearn, Python, R, Keras, Statistical Analysis, Computer Vision, PySpark