
Senior Cloud & ML Infrastructure Engineer
at Hunarstreet technologies pvt ltd
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 forsomeone passionate about solving complex platform engineering challenges across AWS, witha focus on model orchestration, deployment automation, and production-grade reliability. You’llarchitect 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-timeinference 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, andcompliance 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 engineeringteams
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

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