AI Product Owner

Role Overview: Buildings are becoming smarter with connected technologies, leading to increased data accessibility from sensors. Johnson Controls is at the forefront of providing AI-enabled enterprise solutions for optimized energy usage, automatic generation of building insights, and predictive maintenance for devices. The Data Strategy & Intelligence team is seeking a Data Scientist to contribute to developing and deploying machine learning/Generative AI and time series analysis models in production. Key Responsibilities: - Help develop and maintain AI algorithms and capabilities within digital products - Utilize data from commercial buildings to apply machine learning and advanced algorithms for optimizing energy consumption, reducing CO2 emissions, enhancing user comfort, and generating actionable insights for improving building operations - Translate data into direct recommendations for stakeholders - Collaborate with product managers to design new AI capabilities - Explore and analyze available datasets for potential applications - Write Python code to develop ML/Generative AI/time series prediction solutions addressing complex business requirements - Research and implement state-of-the-art techniques in Generative AI solutions - Pre-train and fine-tune ML over CPU/GPU clusters while optimizing for trade-offs - Follow code-quality standards and best practices in software development - Develop and maintain test cases to validate algorithm correctness - Assess failures to identify causes and plan fixes for bugs - Communicate key results to stakeholders - Leverage JIRA to plan work and track issues Qualifications Required: - Bachelor's / Masters degree in Computer Science, Statistics, Mathematics, or related field - 5+ years of experience in developing and deploying ML Models with a proven track record of delivering production-ready ML models - Proficiency with Python and standard ML libraries such as PyTorch, Tensorflow, Keras, NumPy, Pandas, scikit-learn, Matplotlib, Transformers - Strong understanding of ML algorithms and techniques including Regression, Classification, Clustering, Deep Learning, NLP / Transformer models, LLMs, and Time Series prediction models - Experience in developing SOA LLM frameworks and models (Azure OpenAI, Meta Llama, etc), advanced prompt engineering techniques, LLMs fine-tuning/training - Experience in working with cloud-based ML/GenAI model development/deployment on AWS / GCP / Azure - Excellent verbal and written communication skills Additional Details: - Prior Domain experience in smart buildings and building operations optimization - Experience in working with Microsoft Azure Cloud,