MLOps / LLMOps Engineer

Key Responsibilities :

• Design, build, and maintain CI / CD pipelines for ML model training, validation, and deployment
• Automate and optimize ML workflows, including data ingestion, feature engineering, model training, and monitoring
• Deploy, monitor, and manage LLMs and other ML models in production (on-premises and / or cloud)
• Implement model versioning, reproducibility, and governance best practices
• Collaborate with data scientists, ML engineers, and software engineers to streamline end-to-end ML lifecycle
• Ensure security, compliance, and scalability of ML / LLM infrastructure
• Troubleshoot and resolve issues related to ML model deployment and serving
• Evaluate and integrate new MLOps / LLMOps tools and technologies
• Mentor junior engineers and contribute to best practices documentation

Required Skills & Qualifications :

Preferred Skills :

Skills Required

Prometheus, Elk Stack, Bash, Grafana, Jenkins, Devops, Gcp, MLops, Docker, Azure, Kubernetes, Python, Aws