Senior Cloud
1 week ago
Senior Cloud & ML Infrastructure EngineerLocation : Hyderabad PuneExperience : 6+ YearsNOTE : Immediate JoinerAbout the Role : Were 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. Youll 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 teamsRequired 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 OTAdeployments- Experience designing systems for physical robot fleet telemetry, diagnostics, and control- Familiarity with multi-stage production environments and robotic software rolloutprocesses- 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 (ref:hirist.tech)
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