AI Data Scientist

As an AI Data Scientist at Johnson Controls located in Pune, India, you will be an integral part of the Data Strategy & Intelligence team. You will be responsible for developing and deploying machine learning/Generative AI and time series analysis models in production to contribute to optimized energy utilization, auto-generation of building insights, and predictive maintenance for installed devices. To excel in this role, you must possess a deep understanding of machine learning concepts, Large Language Models (LLM), time series models, and have hands-on experience in developing and deploying ML/Generative AI/time series models in a production environment. Your primary responsibilities will include developing and maintaining AI algorithms and capabilities within digital products at Johnson Controls. By leveraging data from commercial buildings and applying advanced algorithms, you will optimize building energy consumption, reduce CO2 emissions, enhance user comfort, and generate actionable insights to improve building operations. Additionally, you will translate data into recommendations for various stakeholders, ensuring that AI solutions deliver robust and repeatable outcomes through well-designed algorithms and software. Collaboration is key in this role, as you will work closely with product managers to design new AI capabilities, explore and analyze datasets, write Python code to develop ML/Generative AI/time series prediction solutions, implement state-of-the-art techniques in Generative AI, and pre-train and finetune ML models over CPU/GPU clusters. You will also uphold code-quality standards, develop test cases to validate algorithm correctness, and communicate key results to stakeholders effectively. The ideal candidate for this position should hold a Bachelor's/Master's degree in Computer Science, Statistics, Mathematics, or a related field, along with at least 5 years of experience in developing and deploying ML models. Proficiency in Python and standard ML libraries such as PyTorch, Tensorflow, and scikit-learn is essential. Moreover, a strong understanding of ML algorithms and techniques, experience in working with cloud-based ML/GenAI model development/deployment, and excellent communication skills are prerequisites for success in this role. Preferred qualifications include prior domain experience in smart buildings and building operations optimization, as well as experience working with Microsoft Azure Cloud.,