EY - GDS Consulting - AIA - AI ML Ops Engineer - Senior

MLOps / LLMOps Engineering

• Design, build, and maintain end‑to‑end MLOps and LLMOps pipelines covering experimentation, training, deployment, monitoring, and retraining.
• Operationalize ML and LLM models for production environments with high availability and scalability.
• Implement best practices for model versioning, artifact management, and reproducibility.

CI/CD & Automation

• Develop and maintain CI/CD/CT pipelines for ML and GenAI workloads.
• Automate model packaging, deployment, validation, and rollback processes.
• Integrate AI pipelines with enterprise DevOps toolchains.

API & Model Serving

• Design, develop, and deploy REST‑based inference services using Python frameworks such as Flask or FastAPI.
• Enable scalable and secure model serving for batch and real‑time use cases.

Monitoring, Governance & Responsible AI

• Monitor model performance, data drift, and model drift in production environments.
• Support Responsible AI practices including robustness, explainability, and governance controls.
• Enable continuous feedback loops and retraining strategies to maintain model quality.

Collaboration & Delivery

• Collaborate with cross‑functional teams including Data Engineering, Data Science, Platform Engineering, and Cyber/Compliance teams.
• Support enterprise AI platforms and GenAI solutions across multiple client engagement