Cloud Platform Engineer Senior Consultant I

Job Description The Allstates Data & Analytics Technology organization is seeking a Machine Learning Platform Lead Engineer to architect, build, and scale the core platforms that power enterprise-wide machine learning solutions. In this role, you will provide deep technical leadership across ML infrastructure, MLOps automation, model deployment systems, and cloud-native engineering. You will influence platform strategy, guide architectural decisions, and collaborate closely with data science, engineering, security, and product teams to enable reliable, scalable, and responsible ML adoption across the enterprise. This role is ideal for a senior technologist who thrives in hands-on engineering, technical leadership, and building high-impact ML platform capabilities. Primary Skill- Cloud Technologies, Machine Learning, Terraform, Devops, CI/CD Exp- 5 to 8Yrs Location- Bangalore, Pune Work from Office (Hybrid) Shift Time- 1Pm to 9.30Pm Key Responsibilities Serve as the technical lead for ML platform architecture, guiding system design, scalability, performance, and reliability across platform components. Architect and build core ML platform services, including training and compute infrastructure, feature stores, model registries, inference runtimes, and data pipelines. Drive architectural decisions for distributed systems, cloud native frameworks, and automated MLOps workflows that support enterprise-scale machine learning. Evaluate and integrate emerging ML platform technologies, tools, and best practices to continuously strengthen platform capabilities. Design and implement robust MLOps pipelines for experiment tracking, data and model versioning, CI/CD for ML, automated retraining, and model governance. Develop automated workflows that ensure reproducible model training, validation, deployment, and lifecycle management across multiple environments. Implement monitoring and observability systems for model performance, data quality, drift detection, and inference reliability. Build and optimize cloud-based ML infrastructure on Azure, AWS, or GCP using Kubernetes, containerization, and infrastructure as code. Develop scalable batch and streaming data pipelines using modern data engineering tools and frameworks. Embed security, compliance, responsible AI principles, and cost optimization best practices within ML platform architecture and operations. Collaborate with data scientists to translate modeling needs into scalable, reusable, and self-service platform capabilities. Work closely with security, compliance, and governance teams to ensure safe and compliant deployment of AI/ML solutions. Partner with application engineering teams to accelerate adoption of ML services and enable consistent, high-quality production deployments. Provide technical mentorship, set engineering standards, and contribute to documentation, best practices, and ongoing platform improvements. Education 4 year Bachelors Degree (Preferred) Experience 5 or more years of experience (Preferred) Supervisory Responsibilities This job does not have supervisory duties. Education & Experience (in lieu) In lieu of the above education requirements, an equivalent combination of education and experience may be considered. Primary Skills Amazon Web Services (AWS), DevOps, GCP Dataflow, Machine Learning (ML), Microsoft Azure, Terraform (Software) Shift Time Shift B (India) Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.