What you will do
Spaces and buildings are getting smarter with connected technologies. With more connectivity, there is access to more data from sensors installed in buildings. Johnson Controls is leading the way in providing Machine Learning enabled enterprise solutions that contribute to optimized energy utilization, auto- generation of building insights and enable predictive maintenance for installed machines and devices. Our OpenBlue AI team is looking for a Data Scientist to join our growing team. You will play a critical role in synthesizing and transforming data and developing and deploying machine learning models in production.
To be successful in this role, the Data Scientist should have a deep knowledge of machine learning concepts, data wrangling tools as well as hands on experience in developing and deploying ML models in production.
How will you do
• Communicate with internal teams to procure / understand available data and utilize the same to develop Machine Learning (ML) models.
• Collaborate with Subject Matter Experts (SME) to set up business context for embedding intelligence in enterprise solutions.
• Build scalable, tractable, and robust ML models according to the committed domain standards.
• Deploy ML models to cloud / targeted devices based on customer requirements.
• Search, identify and produce new industry concepts and functional areas based on refined data from in-house SME Knowledge Base.
What we look for
• Bachelor's / Master’s degree in Computer Science, Statistics, Mathematics, or related field.
• 3+ years of experience of developing and deploying ML Models with a proven record of delivering production ready ML models.
• Proficiency with Python and standard ML libraries viz. PyTorch, Tensorflow, Keras, NumPy, Pandas, Scikit-Learn, Matplotlib, Transformers, FastAPI / Django.
• Understanding of orchestration libraries / tools viz. MlFlow, KubeFlow, Airflow
• Strong understanding of ML algorithms and techniques viz. Regression, Classification, Clustering, Deep Learning, NLP / Transformer models.
• Understanding of Model Optimization Techniques viz. Quantization and Knowledge Distillation.
• Experience with Feature Engineering techniques viz. PCA, Stemming, Lemmatization, Tokenization, Data Augmentation in NLP
• Excellent problem-solving skills and attention to detail, with the ability to effectively communicate technical concepts to both technical and non-technical audiences.
• Experience on working with cloud (AWS / GCP / Azure) based model development / deployment.
• Proficiency in version control systems (e.g., Git) and collaboration tools (e.g., JIRA, Confluence).
Preferred
• Prior Domain experience in Smart buildings and Energy optimization
• Experience in Databricks
• Experience on working with Azure Cloud.
• Experience in developing production-ready backend APIs and data-validation tools.
• Understanding of concept of LLMs, relevant techniques (LoRA, RAG, RLHF, LangChain) and their applications.
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