AI Data Scientist - Pune, India

Johnson Controls is at the forefront of smart building technology, leveraging connected systems to harness vast amounts of data from building sensors. We are developing AI-enabled enterprise solutions focused on optimizing energy consumption, automating building insights, and enabling predictive maintenance. Our Data Strategy & Intelligence team is seeking a talented Data Scientist to join our expanding team in Pune, India. In this pivotal role, you will be instrumental in developing and deploying advanced machine learning, Generative AI, and time series analysis models into production environments.

The Role

To excel in this position, a deep understanding of machine learning principles is essential. This includes extensive knowledge of Large Language Models (LLMs) – covering their training, optimization, and deployment – as well as time series modeling. Practical, hands-on experience in developing and deploying ML, Generative AI, and time series models into production is a key requirement.

What You Will Do

As an AI Data Scientist at Johnson Controls, you will contribute to the development and maintenance of sophisticated AI algorithms and capabilities integrated within our digital products. These applications will process data from commercial buildings, employing machine learning, GenAI, and other advanced algorithms to deliver significant value by:

• Optimizing building energy consumption, occupancy, and reducing CO2 emissions, while enhancing user comfort.
• Generating actionable insights to drive improvements in building operations.
• Translating complex data into clear, direct recommendations for various stakeholders.

Your work will be crucial in ensuring our AI solutions deliver robust, repeatable outcomes through meticulously designed algorithms and well-crafted software. You should be adept at applying machine learning concepts to real-world challenges, effectively managing the complexities inherent in practical datasets.

How You Will Do It

• Contribute actively as a member of the AI team, fulfilling assigned tasks and responsibilities.
• Collaborate closely with product managers to conceptualize and design innovative AI capabilities.
• Explore and analyze available datasets to identify potential applications and opportunities.
• Design and develop ML, Generative AI, and Time-series prediction solutions, demonstrating a clear understanding of intricate business requirements.
• Work in partnership with cross-functional teams to seamlessly integrate AI capabilities into our existing product portfolio.
• Research and implement cutting-edge techniques within the realm of generative AI solutions.
• Develop and maintain robust pipelines for AI model integration.
• Engage in pre-training and fine-tuning ML models on GPU clusters, with a focus on optimizing trade-offs.

What We Look For

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a closely related field.
• A minimum of 7 years of experience in developing and deploying ML models, with a demonstrable track record of delivering production-ready solutions.
• Expert-level proficiency in Python, alongside essential ML libraries such as PyTorch, TensorFlow, Keras, NumPy, Pandas, scikit-learn, Matplotlib, Transformers, and frameworks like FastAPI / Django.
• A strong foundational understanding of ML algorithms and techniques, including Regression, Classification, Clustering, Deep Learning, NLP/Transformer models, LLMs, and Time-series prediction models.
• Proficiency in developing SOA LLM frameworks and models (e.g., Azure OpenAI, Meta LLAMA), advanced prompt engineering, LLM fine-tuning/training, and Retrieval-Augmented Generation (RAG) systems.
• Experience collaborating with engineering teams for the production deployment of ML/LLM models, including model observability and monitoring.
• Hands-on experience with cloud-based ML/GenAI model development and deployment on platforms like AWS, GCP, or Azure.

Preferred Qualifications

• Prior domain experience in Smart Buildings and Energy Optimization.
• Experience working with Azure Cloud.