Key responsibilities -

·         Implementation of end-to-end statistical/ML/analytics solutions as per the industry standard process, CRISP-DM

·         Understand business requirements and propose suitable solutions

·         Explore, devise and implement ML algorithm stack

·         Experiment, prototype and finalize specific solution with the best business metrics

·         Design and implement architecture/tech stack for data integration, data flow and data storage for ML solutions

·         Collaborate with product teams across the organization for deployment and integration of AI solutions in existing products

·         Deliver production quality, modular, reproducible code in Python

·         Create data visualizations to visualize raw data and analytics insights to demonstrate efficacy of the solution

Requirements –

·         Solid understanding of statistics, probability, ML and DL

·         A minimum of 8 years of experience in developing and deploying end-to-end AI/ML solutions in production environment

·         Exposure to reinforcement learning, supervised and unsupervised algorithms, various architectures of neural networks, time series forecasting, deep learning networks

·         Deep expertise in any specific application of ML and DL

·         Prior experience in building and deploying ML pipelines from data ingestion, preparation to deploying models in production

·         An understanding of various databases relational, NoSQL with prior experience in any DB

·         Exposure to ML and DL frameworks like TensorFlow, PyTorch, Caffe, etc

·         Familiarity with ML testing and data validation frameworks

·         A go-getter attitude with a drive for execution

Good to have –

·         Familiarity with IoT communication protocols like MQTT

·         Edge AI deployment experience