Senior Cloud & ML Infrastructure Engineer

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 StepFunctions, 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 devices