Dev / ML Ops

• Cloud Infrastructure Management: Design, implement, and maintain robust, scalable, and cost-efficient cloud solutions on AWS.
• Automation & CI/CD: Build and maintain CI/CD pipelines to automate infrastructure provisioning, application deployments, and system monitoring.
• Monitoring & Optimization: Develop monitoring solutions to ensure performance, reliability, and cost-effectiveness of cloud infrastructure.
• Security: Implement cloud security best practices, including IAM, network configurations, and encryption strategies.
• ML Ops Support: Collaborate with AI team and engineers to operationalize machine learning models, ensuring smooth integration into production systems.
• Containerization & Orchestration: Use tools like Docker to containerize applications and manage clusters effectively.
• Collaboration: Partner with software developers, data engineers, and other stakeholders to streamline workflows and ensure infrastructure aligns with business needs.
• Documentation: Maintain comprehensive documentation of infrastructure, processes, and best practices for internal use and onboarding.

• Experience: 3+ years of experience in DevOps or a related role, with exposure to ML Ops workflows.
• Technical Skills:
• Expertise in AWS services (e.g., EC2, S3, Lambda, EKS, SageMaker).
• Proficiency in Infrastructure as Code (IaC) tools such as Terraform or CloudFormation.
• Hands-on experience with CI/CD tools like GitHub Actions, or GitLab CI/CD.
• Strong skills in containerization (Docker) and orchestration (Kubernetes).
• Proficiency in scripting languages such as Python, Bash, or PowerShell.
• ML Ops Knowledge: Familiarity with SageMaker, Kubeflow, MLflow, or equivalent tools for machine learning operations.
• Monitoring Tools: Experience with observability tools like CloudWatch, Prometheus, Grafana, or similar.
• Problem-Solving: Strong troubleshooting skills for cloud and system-related issues.
• Communication: Clear and effective communication skills to collaborate across technical and non-technical teams.

• Experience managing data engineering workflows or working with platforms like Databricks.
• Knowledge of serverless architecture and event-driven systems.
• Familiarity with cloud cost management tools and strategies.
• Exposure to advanced security compliance frameworks and practices.
• Familiarity with Ruby on Rails