MLOps GenAI Engineer

Tata Consultancy Services; Bengaluru; On-site; INR 4,500,000 - 6,500,000; Full time

Job summary

Tata Consultancy Services seeks an experienced Senior MLOps / GenAI Engineer to design, deploy, and manage ML and GenAI workloads on Google Cloud Platform. You will work with Vertex AI, Kubeflow, and Vertex Pipelines to build scalable pipelines and automate end-to-end ML lifecycles.

The role requires deep expertise in MLOps, automation, and cloud-native AI platforms, plus hands-on skills in TensorFlow, PyTorch, and data processing tools.

Qualifications

• 5+ years in Machine Learning, MLOps, or Data Engineering.
• Hands-on experience with Vertex AI and ML model deployment on GCP.
• Experience building scalable ML/GenAI solutions in cloud environments.
• Strong background in automation, CI/CD, and containerized deployments.

Responsibilities

• Design, develop, and deploy ML and GenAI solutions using Vertex AI.
• Build and manage ML pipelines using Vertex Pipelines and Kubeflow.
• Develop and optimize training workloads, hyperparameter tuning, and model lifecycle management.
• Implement GenAI solutions using Gemini, Agent Builder, Vector Search, and RAG architectures.
• Deploy, monitor, and maintain production ML models with drift detection and explainability.
• Collaborate with data engineering teams using BigQuery, Dataflow, Dataproc, and Spark.
• Automate ML workflows using CI/CD, Terraform, Docker, Kubernetes, and GKE.

Skills

Gemini

Agent Builder

Vector Search

RAG

BigQuery ML

Dataflow

Dataproc

Spark

Python

SQL

Bash

TensorFlow

PyTorch

Scikit-learn

XGBoost

Vertex AI

Kubeflow

Vertex Pipelines

Terraform

Docker

Kubernetes

GKE

Tools

Vertex AI

Kubeflow

Vertex Pipelines

Terraform

Docker

Kubernetes

GKE

Job description

Seeking an experienced Senior MLOps / GenAI Engineer with expertise in building, deploying, and managing Machine Learning and Generative AI solutions on Google Cloud Platform (GCP). The role requires strong experience in Vertex AI, MLOps, model deployment, automation, and cloud-native AI platforms.

Key Responsibilities:

• Design, develop, and deploy ML and Generative AI solutions using Vertex AI.
• Build and manage ML pipelines using Vertex Pipelines and Kubeflow.
• Develop and optimize training workloads, hyperparameter tuning, and model lifecycle management.
• Implement GenAI solutions using Gemini, Agent Builder, Vector Search, and RAG architectures.
• Deploy, monitor, and maintain production ML models with drift detection and explainability.
• Collaborate with data engineering teams using BigQuery, Dataflow, Dataproc, and Spark.
• Automate ML workflows using CI/CD, Terraform, Docker, Kubernetes, and GKE.

Required Skills:

• GenAI: Gemini, Agent Builder, Vector Search, RAG.
• Data Processing: BigQuery ML, Dataflow, Dataproc, Spark.
• Languages: Python, SQL, Bash.
• ML Frameworks: TensorFlow, PyTorch, Scikit-learn, XGBoost.

Experience:

• 5+ years in Machine Learning, MLOps, or Data Engineering.
• Hands-on experience with Vertex AI and ML model deployment on GCP.
• Experience building scalable ML/GenAI solutions in cloud environments.
• Strong background in automation, CI/CD, and containerized deployments