Technical Architect- MLOPs Engineer

Mphasis is seeking an experienced MLOps Engineer to design, build, and manage ML/LLM pipelines using open-source and cloud-native tools. The role involves deploying models on AWS, GCP, or Azure, monitoring performance, and optimizing LLM inference. Candidates should have 10+ years of MLOps experience and strong DevOps skills.

• Design and manage MLOPs and LLMOPs pipelines for data ingestion, training, validation, deployment, and monitoring.
• Set up cloud-native MLOPs pipelines on AWS, GCP, or Azure.
• Monitor models in production using Prometheus, Grafana, and Tensorboard.
• Implement CI/CD pipelines for ML models with GitHub Actions, Jenkins, or GitLab CI.

• 10+ years of experience in MLOps
• Proficiency with Kubernetes and Docker for container orchestration
• Experience with open-source MLOPs tools (MLflow, Kubeflow, DVC) and data versioning
• Hands-on experience with cloud-native ML tools in AWS, GCP, or Azure
• Knowledge of Python or Bash scripting
• Solid understanding of CI/CD practices and tools (GitHub Actions, Jenkins, GitLab CI/CD)
• Proficient in infrastructure-as-code tools like Terraform or Ansible