Cloud AI/ML Architect

4 days ago

Salem, Tamil Nadu, India beBeeMachineLearning Full time ₹ 15,00,000 - ₹ 25,00,000
Job Title: Senior Cloud AI/ML Engineer

About the Role:

We are seeking a highly skilled Senior Cloud AI/ML Engineer to design and implement cutting-edge AI Agents that optimize cloud resource allocation, auto-scaling, and performance tuning.

As a Senior Cloud AI/ML Engineer, you will develop predictive models, automate workflows, and integrate AI-driven insights into mission-critical cloud environments.

  • Design and implement AI Agents to optimize cloud resource allocation, auto-scaling, and performance tuning
  • Develop predictive models for failure detection, incident management, and system health monitoring
  • Automate operational workflows using machine learning and intelligent scripting
  • Integrate AI-driven insights with existing cloud monitoring tools
  • Collaborate with DevOps and SRE teams to deploy, monitor, and improve ML models in production environments
  • Conduct anomaly detection for security, cost optimization, and performance analytics
  • Continuously evaluate emerging AI technologies and tools for operational improvements
  • Maintain documentation and best practices for AI/ML integration in cloud systems

Required Skills and Experience:

  • Bachelor's or equivalent experience or Master's degree in Computer Science, Data Science, or related technical field
  • Proven ability building and deploying ML models, with at least 2 years focused on infrastructure or cloud operations
  • Solid knowledge of hybrid cloud technologies (AWS, GCP, OpenStack, Kubernetes)
  • Experience with Python, Jupyter, and ML libraries such as PyTorch, TensorFlow, or scikit-learn
  • Familiarity with cloud-native monitoring, logging, and automation tools (e.g., Terraform, Ansible, Prometheus, Splunk, App Dynamics)
  • Comfortable working with streaming data, APIs, and telemetry systems
  • Strong communication and multi-functional collaboration skills
  • Experience with Agile and DevOps operating models, including project tracking tools (e.g., Jira), Git (any Version Control systems), and CI/CD systems (e.g., GitLab, GitHub Actions, Jenkins)

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