
Senior Cloud
2 days ago
About The Role
We are seeking a Senior Cloud & ML Infrastructure Engineer to design, scale, and optimize cloud-native machine learning platforms. The role involves architecting large-scale ML systems on AWS, building automation for deployments, and ensuring production-grade reliability. You will work closely with cross-functional teams, bridging DevOps, ML, and backend engineering to enable scalable, cost-efficient, and secure ML infrastructure.
Key Responsibilities
- Architect and manage end-to-end ML infrastructure using AWS SageMaker, Step Functions, Lambda, and ECR
- Build highly available, multi-region AWS solutions for real-time inference & batch processing
- Develop reproducible infrastructure with AWS CDK & IaC best practices
- Establish CI/CD pipelines for ML model packaging, validation, and monitoring
- Ensure compliance, IAM security, and data protection (encryption in transit & at rest)
- Optimize compute & storage usage for performance and cost efficiency
- Integrate ML infrastructure with data lakes and analytics platforms
- Mentor engineering teams on AWS adoption and infrastructure best practices
Required Skills
- 6+ years in AWS cloud infrastructure design & deployment at scale
- Strong experience with ML pipelines (SageMaker, ECS/EKS, or custom Docker workflows)
- Expertise in networking, IAM, VPCs, and AWS security practices
- Proficiency with IaC frameworks (AWS CDK/Terraform) & automation tools
- Advanced scripting in Python, Go, or Bash
- Hands-on with observability stacks (CloudWatch, Prometheus, Grafana)
Nice to Have
- Background in robotics infrastructure (AWS IoT Core, Greengrass, OTA deployments)
- Experience with robot fleet telemetry, diagnostics, and real-time control
- Familiarity with ROS 2, sensor data pipelines, and embedded Linux deployments
- Exposure to edge inference, MQTT, and streaming workflows
- Knowledge of frontend hosting for dashboards/APIs
This is an exciting opportunity for an engineer passionate about scalable ML systems, AWS architecture, and platform reliability, with scope to contribute to next-generation ML & robotics infrastructure.
Skills: python,observability stacks,embedded linux deployments,prometheus,devops,iac,architecting,networking,aws,lambda,frontend hosting,ros 2,eks,ecr,ci/cd pipelines,cloudwatch,infrastructure,data pipelines,aws cdk,ml,iac frameworks,robot fleet telemetry,mqtt,terraform,greengrass,edge inference,grafana,lagom,automation,cloud,bash,iam security,ml infrastructure,aws sagemaker,ota deployments,robotics infrastructure,vpcs
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