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Capgemini

Global consulting, technology services, outsourcing

Vertex AI & GCP Architect

Applied Machine LearningUpdated on Nov 14
Full-timePune, Maharashtra, IndiaNo salary listedIn-person

About the Job

Requirements

  • At least 12 years of total experience.
  • At least 4 years of experience with Google Cloud Platform, including at least 2 years of hands-on experience with Vertex AI.
  • Strong proficiency in Python and machine-learning frameworks including TensorFlow, PyTorch, and scikit-learn.
  • Experience building Vertex AI Pipelines and managing the model lifecycle in Vertex AI Model Registry.
  • Strong Terraform skills for provisioning Vertex AI, Google Cloud Storage, BigQuery, and associated infrastructure.
  • Good understanding of Google Cloud IAM, particularly for securing machine-learning pipelines and data access.
  • Experience with Google Cloud-native development patterns and event-driven architectures.
  • Demonstrated cloud delivery experience, including planning, execution, and stakeholder management.
  • Familiarity with containerization using Docker and Google Kubernetes Engine for model serving.

Responsibilities

  • Design and implement end-to-end MLOps pipelines on Vertex AI, including data ingestion, model training, evaluation, and deployment.
  • Build and manage Vertex AI Pipelines using Kubeflow Pipelines for automated model training and retraining workflows.
  • Deploy and manage models using Vertex AI Model Registry, Endpoints, and Batch Prediction services.
  • Implement feature-engineering workflows using Vertex AI Feature Store.
  • Develop Google Cloud-native integrations connecting Vertex AI with BigQuery, Dataflow, Cloud Storage, and Pub/Sub.
  • Manage infrastructure for machine-learning workloads using Terraform, ensuring reproducible and version-controlled environments.
  • Configure IAM policies for Vertex AI workloads, including service-account governance and VPC Service Controls.
  • Lead cloud delivery activities, including sprint planning, release management, environment promotion, and stakeholder communication.
  • Establish model monitoring using Vertex AI Model Monitoring for data-drift and skew detection.
  • Collaborate with data scientists to containerize experiments and promote models through development, staging, and production environments.
  • Drive adoption of Google Kubernetes Engine for model-serving workloads where custom inference infrastructure is required.

About the Company

Capgemini

Global consulting, technology services, outsourcing

Capgemini provides consulting, technology services, and outsourcing to help organizations transform digitally. Its offerings include strategy and transformation consulting, system integration, application development, IT infrastructure management, and managed IT operations. It differentiates itself with a global presence in over 50 countries and a focus on applying AI, cloud, and cybersecurity to real business problems. Its goal is to help clients navigate digital transformation and improve efficiency and innovation through tailored, contract-based or managed services.

Company size
10,001+
Company stage
IPO
Headquarters
Paris, France
Founded
1967

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