MLOps Engineer

Job Description - MLOps Engineer (46 Years)

We are seeking an experienced MLOps Engineer with strong expertise in LLM deployment, optimization, and scalable model serving. The ideal candidate will work at the intersection of AI / ML engineering, DevOps, and cloud infrastructure, ensuring seamless integration of large-scale AI models into production.

Responsibilities :

• Design, deploy, and manage Large Language Models (LLMs) in production environments.
• Build and optimize scalable ML pipelines for training, fine-tuning, and inference.
• Implement MLOps best practices including CI / CD for ML, experiment tracking, and automated retraining workflows.
• Optimize model performance through quantization, pruning, distillation, and GPU / TPU acceleration.
• Manage and monitor LLM serving infrastructure with Kubernetes, Docker, and orchestration tools.
• Collaborate with data scientists and researchers to integrate models into real-world applications.
• Ensure reliability, scalability, and security of deployed ML systems.
• Implement observability and monitoring for model performance, drift detection, and resource utilization.

Key Skills & Experience :

Preferred :

(ref : hirist.tech)