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MLOPs Engineer
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Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Explore the full job description below to learn more about the MLOPs Engineer role, its key responsibilities, and what it's like to be part of our team. If you're excited by what you see, we'd love to hear from you. Apply today and take the next step in your career journey.
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Capgemini is an AI-powered global business and technology transformation partner, delivering tangible business value. We imagine the future of organizations and make it real with AI, technology and people. With our strong heritage of nearly 60 years, we are a responsible and diverse group of 420,000 team members in more than 50 countries. We deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2024 global revenues of €22.1 billion.
Make it real |
Job ID: 152364005
Skills:
Github, BigQuery, Google Cloud Platform, Cloud Storage, Jenkins, Git, MLops, Terraform, Python, Logging, Alerting, Cloud Build, CI CD, Cloud Monitoring, Pub Sub, GitHub Actions, Model Monitoring, ML Lifecycle Management, Model Deployment, Vertex AI, GitLab CI CD, Infrastructure-as-Code
Skills:
Docker, Azure, Helm, Kubernetes, CI CD Pipelines, Observability Monitoring, GitOps, Azure OpenAI, Service Reliability Engineering Practices, Kubeflow, ArgoCD, LLM-Based Services, Azure AI Search, RAG Architectures
Skills:
Prometheus, Elk Stack, Artifactory, Grafana, Docker, Gitlab, Kubernetes, Python, AWS, TensorFlow Serving, Gitflow, TorchServe, ML frameworks
Skills:
Aws Lambda, Python Automation, Cloudformation, Jenkins, Git, MLops, Docker, Terraform, Databricks, Training Pipelines, Feature Store, MLflow, Kubernetes EKS, Model Retraining, SageMaker, Model Monitoring, Drift Detection, Model Deployment, Kubeflow, Inference Pipelines, CI CD for ML
Skills:
Tensorflow, Gcp, Pytorch, Docker, Azure, Kubernetes, Python, AWS, Scikit-learn
