AI/ML Platform Engineer - Pune, Maharashtra, India

Johnson Controls is seeking a skilled ML Platform Engineer specializing in AI & Data Platforms to join our team in Pune, Maharashtra, India. This role focuses on ML Platform Engineering and MLOps, with a strong emphasis on Azure.

ML Platform Engineering & MLOps (Azure-Focused)

• Design, build, and manage end-to-end Machine Learning (ML) and Large Language Model (LLM) pipelines on Azure ML.
• Leverage Azure DevOps for continuous integration, continuous deployment (CI/CD), testing, and release automation.
• Operationalize LLMs and generative AI solutions (e.g., GPT, LLaMA, Claude), prioritizing automation, security, and scalability.
• Develop and manage infrastructure as code (IaC) using Terraform for provisioning compute clusters (e.g., Azure Kubernetes Service (AKS), Azure Machine Learning compute), storage, and networking.
• Implement robust model lifecycle management, including versioning, monitoring, and drift detection, utilizing Azure-native MLOps components.

Infrastructure & Cloud Architecture

• Design highly available and performant serving environments for LLM inference using Azure Kubernetes Service (AKS) and Azure Functions or App Services.
• Build and manage Retrieval-Augmented Generation (RAG) pipelines, integrating vector databases (e.g., Azure Cognitive Search, Redis, FAISS) and orchestrating with frameworks like LangChain or Semantic Kernel.
• Ensure consistent implementation of security measures, logging, role-based access control (RBAC), and audit trails across all environments.

Automation & CI/CD Pipelines

• Develop reusable Azure DevOps pipelines for deploying ML assets, including data pre-processing, model training, evaluation, and inference services.
• Utilize Terraform to automate the provisioning of Azure resources, ensuring consistent and compliant environments for data science and engineering teams.
• Integrate automated testing, linting, monitoring, and rollback mechanisms into the ML deployment pipeline.

Collaboration & Enablement

• Collaborate closely with Data Scientists, Cloud Engineers, and Product Teams to deliver production-ready AI features.
• Contribute to solution architecture for real-time and batch AI use cases, such as conversational AI, enterprise search, and summarization tools powered by LLMs.
• Provide technical guidance on cost optimization, scalability patterns, and high-availability ML deployments.

Qualifications & Skills

Required Experience

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• Minimum of 5 years of experience in ML engineering, MLOps, or platform engineering roles.
• Strong experience deploying machine learning models on Azure, utilizing Azure ML and Azure DevOps.
• Proven experience managing infrastructure as code with Terraform in production environments.

Technical Proficiency

• Proficiency in Python (PyTorch, Transformers, LangChain) and Terraform.
• Scripting experience in Bash or PowerShell.
• Experience with Docker and Kubernetes, particularly within Azure (AKS).
• Familiarity with CI/CD principles, model registry, and ML artifact management using Azure ML and Azure DevOps Pipelines.
• Working knowledge of vector databases, caching strategies, and scalable inference architectures.

Soft Skills & Mindset

• Systems thinker capable of designing, implementing, and improving robust, automated ML systems.
• Excellent communication and documentation skills, bridging the gap between platform and data science teams.
• Strong problem-solving mindset with a focus on delivery, reliability, and business impact.

Preferred Qualifications

• Experience with LLMOps, prompt orchestration frameworks (LangChain, Semantic Kernel), and open-weight model deployment.
• Exposure to smart buildings, IoT, or edge-AI deployments.
• Understanding of governance, privacy, and compliance concerns in enterprise Generative AI use cases.
• Azure certifications (e.g., Azure Solutions Architect, Azure AI Engineer) or Terraform Associate certification are a plus.