Senior Cloud & ML Infrastructure Engineer -Rz

Senior Cloud & ML Infrastructure Engineer Location: Bangalore / Bengaluru, Hyderabad, Pune, Mumbai, Mohali, Panchkula, Delhi Experience: 6–10+ Years Night Shift - 9 pm to 6 am About The Role We're looking for a Senior Cloud & ML Infrastructure Engineer to lead the design, scaling, and optimization of cloud-native machine learning infrastructure. This role is ideal for someone passionate about solving complex platform engineering challenges across AWS, with a focus on model orchestration, deployment automation, and production-grade reliability. You'll architect ML systems at scale, provide guidance on infrastructure best practices, and work cross-functionally to bridge DevOps, ML, and backend teams. Key Responsibilities Architect and manage end-to-end ML infrastructure using SageMaker, AWS Step Functions, Lambda, and ECR Design and implement multi-region, highly-available AWS solutions for real-time inference and batch processing Create and manage IaC blueprints for reproducible infrastructure using AWS CDK Establish CI/CD practices for ML model packaging, validation, and drift monitoring Oversee infrastructure security, including IAM policies, encryption at rest/in-transit, and compliance standards Monitor and optimize compute/storage cost, ensuring efficient resource usage at scale Collaborate on data lake and analytics integration Serve as a technical mentor and guide AWS adoption patterns across engineering teams Required Skills 6+ years designing and deploying cloud infrastructure on AWS at scale Proven experience building and maintaining ML pipelines with services like SageMaker, ECS/EKS, or custom Docker pipelines Strong knowledge of networking, IAM, VPCs, and security best practices in AWS Deep experience with automation frameworks, IaC tools, and CI/CD strategies Advanced scripting proficiency in Python, Go, or Bash Familiarity with observability stacks (CloudWatch, Prometheus, Grafana) Nice To Have Background in robotics infrastructure, including AWS IoT Core, Greengrass, or OTA deployments Experience designing systems for physical robot fleet telemetry, diagnostics, and control Familiarity with multi-stage production environments and robotic software rollout processes Competence in frontend hosting for dashboard or API visualization Involvement with real-time streaming, MQTT, or edge inference workflows Hands-on experience with ROS 2 (Robot Operating System) or similar robotics frameworks, including launch file management, sensor data pipelines, and deployment to embedded Linux device Skills: sagemaker,ci,ros,aws,lambda,aws step functions,cloud,pipelines,ml,cd