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Apply in 3 Minutes : Senior AI / ML Engineer (Infrastructure)

Apply in 3 Minutes : Senior AI / ML Engineer (Infrastructure)

Rapid7Pune, Maharashtra, India
22 hours ago
Job description

⚙️ Senior CloudOps, MLops Infrastructure Engineer Job Description ⚙️

Join Rapid7 : Secure the Future with AI

Overview

We are seeking an experienced and highly specialised Senior MLops Infrastructure Engineer to manage, automate, and secure our production cloud infrastructure and Machine Learning (ML) / Large Language Model (LLM) operational pipelines. This role is strictly focused on the operations and infrastructure that support our data science and engineering teams—it is not a data science or core LLM development position.

Key Responsibilities and Required Expertise

The successful candidate will be an expert in all the following areas, driving high availability, scalability, and security.

I. Cloud Infrastructure & Automation

  • Infrastructure as Code (IaC) : Deep expertise in managing and provisioning infrastructure using Terraform.
  • Containerization & Orchestration : Advanced deployment, scaling, and management of services using Docker / Kubernetes.
  • Networking & Services : Architecting and maintaining high-performance API Layers & Microservices.
  • AWS CloudOps : Expert proficiency in AWS operational services, including EventBridge and Step Functions, for building robust automation flows.
  • Data Storage : Managing and optimizing critical AWS data services, including S3, DynamoDB, Redshift, and Kinesis.

II. MLOps Tooling & Monitoring

  • ML / LLM Tooling Support : Provide and maintain the operational infrastructure for ML / LLM systems, including Model Registry / Versioning tools like MLflow / SageMaker.
  • Pipeline Automation (CI / CD) : Designing and implementing robust CI / CD pipelines for ML / LLM deployments using tools like GitHub Actions / Jenkins.
  • Model Operations : Building the infrastructure to support Drift Detection & Retraining capabilities.
  • Monitoring & Alerting : Implementing comprehensive observability stacks using Prometheus / Grafana / CloudWatch.
  • Incident Management : Leading resolution efforts for production issues, including expertise with PagerDuty and On-call responsibilities.
  • III. Security & Compliance (FinOps)

  • Cloud Security : Establishing and enforcing strong security policies and best practices across the cloud environment (IAM, VPC, Secrets).
  • AWS Security Services : Expert knowledge and application of specific AWS security tools like IAM, KMS, and Secrets Manager.
  • Cost Optimization : Leading initiatives for Cost Optimization (FinOps), balancing performance and efficiency across all cloud resources.
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