DevOps Engineer AI/ML

at  Cisco Systems

WHO WE ARE

CollabAI is a team of AI/ML professionals within Cisco Collaboration. Originally four separate acquisitions, joined into a single group to consolidate expertise in multiple ML domains.
CollabAI strives to stay at the forefront of AI technology, focusing on building and deploying ML and AI features to add intelligence to our Webex Suite. This includes enhancement of audio quality, computer vision, natural language processing using generative ai and large language models, and much more.
CollabAI creates a bridge to AI features for other teams throughout Cisco by collaborating with our tools and expertise. We empower diverse teams to deliver AI/ML experiences across the Webex Suite and beyond.
We are expanding our existing platform team to provide better support for ML based microservices and improving the developer experience of the CollabAI group.

• Understand common security risks and take steps to mitigate them.
• Continuously learn and refine best-practices as the DevOps landscape changes.
• Build good working relationships both inside and outside of your immediate working group. Working with Data, ML, and Software engineers, along with their Product Management counterparts to understand functionality, scalability, performance, security, and integration requirements.
• Configure and deploy cloud-based ML applications taking into account cost, scalability, and maintainability.
• May lead projects with limited complexity to execute defined platform engineering roadmap.
• Recommend expansion and improvement to current systems.
• Implement required review processes into our workflows to ensure regulatory compliance.
• Use configuration management software to deploy updates into the cloud environment.
• Contribute to the design, build, and maintenance of application infrastructure automation.
• Provide Peer review on code written by team members.
• Improve developer experience by delivering automation or infrastructure components to improve efficiency, with a focus on MLOps and reducing the ML iteration loop.
• Maintain and expand our CI/CD automation facilities.
• Monitor and respond to service alerts, trouble-shooting distributed systems using monitoring and logging tools.
• Ensure appropriate testing is conducted prior to deployment of cloud based applications.