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GCP Engineer with AI & ML (4+years experience)

4 years

0 Lacs

Chennai Tamil Nadu India

Posted:2 weeks ago| Platform: Linkedin logo

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Skills Required

gcp ai ml technology engineering learning deployment automation data devops software drive design model training vertex dataflow storage iam automate provisioning terraform optimization tuning support versioning testing monitoring compliance governance security collaboration documentation scripting rollback containerization orchestration kubernetes jenkins gitlab code certifications tensorflow pytorch communication

Work Mode

On-site

Job Type

Full Time

Job Description

Google Cloud Platform (GCP) Engineer with AI/ML expertise

Key Responsibilities:

Cloud Infrastructure (GCP)

  • Design, implement, and manage scalable, secure, and high-performance infrastructure on

    Google Cloud Platform

    .
  • Build and optimize CI/CD pipelines for ML model training and deployment.
  • Develop and maintain

    GCP services

    such as GKE, BigQuery, Cloud Functions, Vertex AI, Dataflow, Pub/Sub, Cloud Storage, IAM, and Cloud Composer.
  • Automate infrastructure provisioning using

    Terraform, Deployment Manager

    , or similar IaC tools.
  • Monitor system performance, cost optimization, and ensure high availability and disaster recovery.

AI/ML Engineering

  • Collaborate with Data Science teams to

    operationalize ML models

    and deploy them into production using

    Vertex AI

    or Kubeflow Pipelines.
  • Implement and manage

    ML workflows

    , including data ingestion, training, tuning, and serving.
  • Support

    MLOps

    practices including versioning, testing, and monitoring of ML models.
  • Ensure compliance with model governance, security, and ethical AI practices.

Collaboration & Support

  • Provide technical mentorship to junior engineers and ML Ops professionals.
  • Work with cross-functional teams including product, engineering, and data to ensure timely delivery of projects.
  • Create documentation, knowledge bases, and SOPs for deployment and operations processes.

Required Qualifications

  • Bachelor’s or Master’s degree

    in Computer Science, Engineering, Data Science, or a related field.

  • 4+ years of professional experience

    in cloud engineering or AI/ML infrastructure, with at least 2 years on GCP.
  • Hands-on experience with

    GCP tools

    such as Vertex AI, BigQuery, GKE, Cloud Functions, and Dataflow.
  • Proficient in

    Python

    ,

    SQL

    , and scripting for automation and data processing.
  • Strong knowledge of

    MLOps principles

    , model versioning, monitoring, and rollback strategies.
  • Experience with

    containerization (Docker)

    and orchestration (Kubernetes/GKE).
  • Familiarity with

    CI/CD tools

    (e.g., Jenkins, Cloud Build, GitLab CI/CD).
  • Experience with

    infrastructure as code (IaC)

    tools like

    Terraform

    or

    Ansible

    .

Preferred Qualifications

  • GCP certifications such as

    Professional Cloud Architect

    ,

    Professional Data Engineer

    , or

    Machine Learning Engineer

    .
  • Experience with

    real-time data processing

    and

    streaming analytics

    (e.g., using Pub/Sub + Dataflow).
  • Familiarity with

    data governance

    ,

    security best practices

    , and

    GDPR/PII compliance

    in ML applications.
  • Exposure to

    multi-cloud or hybrid cloud environments

    .
  • Knowledge of ML frameworks like TensorFlow, PyTorch, Scikit-learn, or XGBoost.

Key Competencies

  • Strong problem-solving skills and analytical thinking.
  • Excellent communication and collaboration abilities.
  • Proactive mindset with a focus on innovation and continuous improvement.
  • Adaptable in a fast-paced, evolving technological environment.



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