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

Senior Cloud & ML Infrastructure Engineer -Rz