Machine Learning Engineer

Experience- 5 to 10 years

Location- HYD

Work timings- 2 PM to 11 PM IST

Working from client – all 5 days

DBS/DBS-/2025/2778559

MLOps Engineer

Responsibilities

• Data and Feature Pipelines:

  Design, build, and manage automated data ingestion, transformation, and validation pipelines using services like

  Kubeflow Pipelines

  and

  Vertex AI Pipelines

  .

• Feature Engineering:

  Implement and containerize feature engineering logic for diverse datasets, ensuring reusability and scalability.

• Data Validation:

  Integrate and manage data validation processes, including leveraging advanced techniques like

  AI Agents

  and the

  Generative Language API

  to automatically detect and remediate data quality issues.

• Model Training and Experimentation:

• Set up and maintain automated continuous training (

  CT

  ) pipelines using

  Vertex AI Pipelines

  (Schedules) and

  Cloud Scheduler

  .
• Implement

  experiment tracking

  to log and compare model parameters, metrics, and artifacts.
• Configure and execute

  Hyperparameter Tuning

  jobs using

  Vertex AI Training

  to optimize model performance.

• Model Management:

  Establish a robust

  Model Versioning

  system to manage and store model artifacts securely in a centralized repository (

  Cloud Storage

  ).

• Deployment and Serving:

• Containerize ML models and their dependencies using

  Docker

  and manage images with

  Artifact Registry

  .
• Build and maintain

  CI/CD

  workflows for ML models, ensuring seamless and automated deployment.
• Configure and manage low-latency production serving environments using

  Vertex AI Endpoints

  for real-time inference.