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 2 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