Johnson Controls
Produces HVAC, fire, security and building automation systems to optimize and protect buildings globally.
AI Engineer
Develop and deploy AI/ML models, pipelines, and MLOps solutions for smart building tech.
Job Highlights
About the Role
The AI Engineer will design, develop, and implement AI models and algorithms to solve complex business challenges such as computer vision, natural language processing, and predictive analytics. They will collaborate with data scientists and software engineers to transition models from research prototypes to scalable production environments, building and maintaining robust machine learning pipelines for data ingestion, transformation, and model retraining. Deployment will involve cloud platforms (AWS, Azure, GCP) using MLOps practices and containerization tools like Docker and Kubernetes, while monitoring, testing, and optimizing performance, accuracy, and efficiency of deployed models. • Design and develop AI models for computer vision, NLP, and predictive analytics • Collaborate with data scientists and engineers to move prototypes to production • Build and maintain scalable ML pipelines for data ingestion, transformation, and retraining • Deploy solutions on AWS, Azure, or GCP using MLOps, Docker, and Kubernetes • Monitor, test, and optimize model performance, accuracy, and efficiency • Ensure AI systems are secure, ethical, and well‑documented • Stay current with AI research and integrate emerging technologies (Generative AI, LLMs, RAG) • Communicate AI capabilities to cross‑functional teams and stakeholders
Key Responsibilities
- ▸model development
- ▸ml pipelines
- ▸cloud deployment
- ▸mlops
- ▸model monitoring
- ▸stakeholder communication
What You Bring
Job Title: AI Engineer. We are seeking an innovative AI Engineer to develop and deploy cutting-edge artificial intelligence and machine learning models that automate processes, generate valuable insights, and enhance user experiences. The ideal candidate will bridge the gap between data science and software engineering, bringing AI prototypes to life in a scalable production environment. Required skills include proven hands‑on experience building, training, and deploying ML models in production, strong programming proficiency in Python, Java, or C++, and familiarity with ML frameworks and libraries. Candidates should have knowledge of cloud computing platforms and MLOps tools, a solid understanding of machine learning algorithms, neural networks, deep learning, and data analysis, as well as excellent problem‑solving, analytical, and communication abilities. Preferred qualifications cover experience in NLP, computer vision, reinforcement learning, big data technologies such as Hadoop or Spark, and familiarity with database design and API development. • Required: hands‑on experience deploying ML models, proficiency in Python/Java/C++, ML frameworks, cloud platforms, and MLOps tools • Strong understanding of machine learning algorithms, deep learning, data analysis, and problem‑solving • Preferred: experience in NLP, computer vision, reinforcement learning, Hadoop/Spark, and SQL/NoSQL database/API development
Requirements
- ▸python
- ▸ml frameworks
- ▸cloud
- ▸mlops
- ▸deep learning
- ▸nlp
Work Environment
Onsite