ML Engineer - GCP

Skills: Digital – Google Cloud | Digital – Azure Machine Learning (ML)

We are seeking an experienced MLOps Engineer responsible for building, automating, and managing scalable machine learning pipelines and deployments on Google Cloud Platform
.

The ideal candidate will have strong expertise in cloud platforms, ML engineering, data pipelines, CI/CD, containerization, monitoring, and security to support end-to-end ML lifecycle management.

• Hands-on experience with:

  • Vertex AI (AI Platform)

  • Cloud Storage

  • Big Query

  • Cloud Functions

  • Cloud Pub/Sub

  • Cloud Build

  • Airflow

  • Cloud Run

• Element platform visibility and operational awareness

• Strong understanding of:

  • ML concepts and LLMs (training, validation, hyperparameter tuning, evaluation)

• Experience with :

  • Tensor Flow

  • Keras

  • Py Torch

  • scikit-learn

• Data preprocessing, ETL, and pipeline development

• Experience with PySpark/Scala using serverless Dataproc

• Knowledge of CI/CD tools such as:

  • Looper

  • Jenkins

• Model versioning and continuous training

• Deployment using Vertex AI Pipelines

• Strong programming skills in:

  • Python

  • Bash

  • SQL

• Automation of ML workflows and pipelines

• Containerization using:

  • Docker

• Orchestration using:

  • Kubernetes (GKE)

• Good to have:

  • Helm charts

  • YAML-based Kubernetes deployments

• Experience with :

  • Cloud Monitoring

  • Cloud Logging

  • Prometheus

  • Grafana

• Model performance monitoring using Vertex AI Model Monitoring

• Understanding of:

  • VPC

  • Firewall rules

  • Service accounts

• Secrets management using Secret Manager

• Strong understanding of:

  • General data science methodologies

  • Model development lifecycle

  • ML experimentation and validation practices

• Cloud-native ML deployment expertise

• MLOps lifecycle management

• Scalable data pipeline development

• CI/CD implementation for ML workloads

• Strong Dev Ops and automation mindset