DevOps/MLOps Specialist

Overview

DevOps/MLOps Specialist to design and implement end-to-end MLOps and LLMOps pipelines for large language models in production cloud environments.

What you'll do

• Lead design and implementation of end-to-end MLOps and LLMOps pipelines from development to deployment.
• Develop automation for model deployment and management to improve scalability, efficiency, and cost-effectiveness.
• Implement and manage CI/CD pipelines for ML and LLM models integrated into production.
• Build data pipelines and workflows for training and serving models using orchestration tools.
• Create monitoring systems to track model performance and reliability for ML and LLM systems.
• Optimize deployed model performance for cost, speed, accuracy, and hardware acceleration.
• Maintain model version control, governance, and lifecycle management for ML and LLM models.

What you'll need

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
• 5+ years of experience in MLOps.
• At least 2 years working specifically with LLMOps pipelines for large language models.
• Experience deploying, managing, and optimizing machine learning models in cloud environments at scale.
• Proficiency with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
• Experience with CI/CD pipelines and tools such as Jenkins, GitLab CI, or CircleCI, and automation tools like Terraform or Ansible.
• Hands-on model serving and monitoring using tools such as TensorFlow Serving, TorchServe, Kubeflow, MLflow, Prometheus, and Grafana.