GCP MLOps Engineer; Vertex AI

Role Description s:
Expertise in cloud platforms| ML engineering| data pipelines| and CICD for deploying and managing machine learning solutions.

Skill required

1.Cloud Platforms Services (Google Cloud)

• oGoogle Cloud Platform (GCP) services AI Platform (Vertex AI)| Cloud Storage| Big Query| Cloud Functions| Cloud Pub Sub| Cloud Build| Airflow| and Cloud Run.

• oElement Platform visibility

2.ML Data Engineering

• oUnderstanding of ML concepts and LLMs (training| validation| hyperparameter tuning| evaluation).

• oExperience with Tensor Flow| Keras| PyTorch| and scikit-learn.

• oData preprocessing| ETL| and data pipelines using pyspark
  
  Scala using serverless dataproc

3.CICD for ML (MLOps)

• oKnowledge of CICD tools Looper pro Jenkins.

• oModel versioning| continuous training| and deployment using Vertex AI pipelines.

4.Automation Scripting

• oStrong programming skills in Python| Bash| and SQL

• oAutomation of workflows and ML pipelines.

5.Dev Ops Containerization

• oKubernetes (GKE) and Docker for containerization and orchestration.

• oGood to have Helm charts and YAML for Kubernetes deployments.

6.Monitoring Observability

• oCloud Monitoring| Cloud Logging| Prometheus| and Grafana for monitoring and alerting.

• oModel performance monitoring with Vertex AI Model Monitoring.

7.Security Compliance

• oUnderstanding of VPC| firewall rules| and service accounts.

• oManaging secrets using Secret Manager.

8.Data Science

• oMust understand general data science methods and the development life cycle

An ML Ops Engineer responsible for building| automating| and managing scalable machine learning pipelines and deployments on Google Cloud Platform.