Location : Bangalore, Chennai, Hyderabad, Pune

Role : MLOPS GCP Data Engineer

EXP : 10-19 yrs

Job Summary :

We are seeking a highly skilled MLOps Engineer with robust expertise in the Google Cloud Platform (GCP) ecosystem, including Vertex AI, GKE, and LLMOps. The ideal candidate will design, build, and optimize ML pipelines, enabling scalable, reliable, and secure deployment of machine learning models in production.

Key Responsibilities :

- Design and implement end-to-end ML pipelines leveraging GCP services (Vertex AI, BigQuery, Dataflow, Pub/Sub, Cloud Storage).
- Deploy, scale, and manage ML models on Vertex AI Prediction, GKE, and Cloud Run.
- Enable LLMOps practices for deploying, fine-tuning, and monitoring Large Language Models (LLMs).
- Implement CI/CD workflows for ML models, ensuring reproducibility, automation, and governance.
- Manage feature stores, model versioning, and experiment tracking using Vertex AI and ML metadata tools.
- Monitor ML systems for model drift, performance degradation, and cost optimization.




- Collaborate with data engineering and data science teams to ensure seamless integration of ML pipelines into enterprise systems.
- Apply MLOps best practices for model security, compliance, and lifecycle management.

Required Skills & Qualifications :

- 5-10 years of experience in MLOps, Data Engineering, or ML Platform Engineering.
- Strong hands-on expertise with Vertex AI, GKE, Kubernetes, and CI/CD pipelines.
- Experience with LLMOps (deploying and managing large language models).
- Proficiency in Python, SQL, and containerization (Docker, Kubernetes).
- Strong understanding of ML lifecycle management, model monitoring, and observability.
- Knowledge of data processing frameworks (Dataflow, Apache Beam, Airflow/Composer).
- Experience with GCP IAM, networking, and security best practices.

Preferred : GCP certifications such as Google Cloud Machine Learning Engineer (MLE) or Professional Data Engineer.

📌 Infometry - Senior MLOps Engineer - GCP Ecosystem (India)
🏢 Infometry
📍 India