Staff AI Ops Engineer

Job Description

Calix is seeking a highly skilled Staff AI Ops Engineer to join our cutting-edge AI/ML team. In this role, you will be responsible for building, scaling, and maintaining the infrastructure that powers our machine learning and generative AI applications. You will work closely with data scientists, ML engineers, and software developers to ensure our ML/AI systems are robust, efficient, and production ready.

Key Responsibilities:

• Lead the implementation and maintenance of maintain scalable infrastructure for ML and GenAI applications.
• Oversee DevOps practices, including the design and management of CI/CD pipelines for AI model deployments
• Manage container orchestration and scaling using Kubernetes, ensuring high availability and security in production environments
• Scale compute resources across CPU/GPU architectures to meet performance requirements
• Implement container orchestration with Kubernetes
• Architect and optimize cloud resources on GCP for ML training and inference
• Setup and maintain runtime frameworks and job management systems (Airflow, KubeFlow, MLflow, etc.)
• Establish monitoring, logging and alerting for systems observability
• Optimize system performance and resource utilization for cost effciency
• Develop and enforce AIOps best practices across the organization

Qualifications:

• Bachelor's degree in computer science, Information Technology, or a related field (or equivalent experience).
• 8+ years of overall software engineering experience
• 5+ years of focused experience in DevOps/AIOps or similar ML infrastructure roles
• Strong experience with containerization and orchestration using Docker and Kubernetes
• Demonstrated expertise in cloud infrastructure management, preferably on GCP
• proficiency with workflow management such as Airflow & Kubeflow
• Strong CI/CD expertise with experience implementing automated testing and deployment pipelines
• Experience with scaling distributed compute architectures utilizing various accelerators (CPU/GPU)
• Solid understanding of system performance optimization techniques
• Experience implementing comprehensive observability solutions for complex systems
• Knowledge of monitoring and logging tools (Prometheus, Grafana, ELK stack).
• Strong proficiency in Python
• Proficient in at least one of the following performance-oriented programming languages: C, C++, Go, Rust.
• Familiarity with ML frameworks such as PyTorch and ML platforms like Vertex AI
• Excellent problem-solving skills and ability to work independently.
• Strong communication skills and ability to work effectively in cross-functional teams 

Location

India – (Flexible hybrid work model - work from Bangalore office for 20 days in a quarter