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Design and deploy ML models using Python, TensorFlow/PyTorch, and MLOps tools; collaborate with data scientists to build scalable AI systems for real-world applications.
Build and automate cloud infrastructure for AI/ML models and agents, deploying scalable pipelines on AWS/GCP/Azure with Kubernetes, CI/CD, and observability tools.
Build and scale MLOps infrastructure for AI/ML pipelines, including CI/CD, model training/inference, and monitoring to improve AI model deployment velocity.
We are GFT Poland. WE KNOW how to tackle complex issues with innovative approach to deliver the highest value. Our reputation has been built around one simple rule: we do not overpromise, WE DELIVER . We deliver to our…
Overview Medallia is the pioneer and market leader in Experience Management. Our award-winning SaaS platform, Medallia Experience Cloud, leads the market in the management of experiences, insights, and actions for…
Build and deploy ML models and MLOps pipelines using TensorFlow, PyTorch, and Scikit-learn to power a scalable AI product used daily by major Brazilian companies.
Leads a DevOps/Platform Engineering team to transform a proprietary AI-driven market model into a Kubernetes-native, self-service infrastructure platform, focusing on scalability, observability, and cross-functional enablement for rapid internal delivery.
Design and deploy AI/ML systems (Generative AI, NLP, vision, recommendations) end-to-end, from data pipelines to cloud production, and mentor engineers.
Design and run Absa’s multi-cloud AI platform (AWS Bedrock, Databricks, Azure AI Foundry) that powers 43 live AI projects across ten countries, focusing on FinOps, zero-trust security, agentic AI infrastructure, and enterprise-grade observability.
Build and run a secure, multi-cloud AI platform for a bank, deploying services on AWS Bedrock, Databricks, Azure AI, Hugging Face and Kubernetes while optimizing costs, security and observability for enterprise-scale AI workloads.
Designs and operates GCP-based data pipelines, AI/ML models, and cloud-native platforms using Dataflow, Kubeflow, BigQuery, and Django, while applying DevOps/MLOps best practices in a defence-focused environment.
Build and deploy AI/ML pipelines on GCP and Azure, operationalizing models into scalable IT solutions using Python, SQL, Kubeflow, and BigQuery.
About the Company: We're not here to run campaigns. We're here to help businesses build legacies. OOm is one of Singapore's leading performance digital marketing agencies, and we've been growing…
Lead the design and deployment of production-grade ML/AI systems using Azure ML, Databricks, and PySpark, ensuring scalable, reproducible, and monitored models in a CI/CD/CT pipeline.
Build and maintain CI/CD pipelines, containerize applications, and optimize cloud infrastructure to deploy and monitor multi-agent media tools using MLOps/DevOps practices.
Lead a team managing GPU clusters and multi-cloud infrastructure for training and deploying generative AI models, including digital humans and voice synthesis, using Kubernetes, Terraform, and GCP.
Build and automate ML pipelines, deploy models to production, and manage cloud infrastructure using DevOps tools like Docker, Kubernetes, and CI/CD.
Build and maintain CI/CD pipelines and ML infrastructure for a team shipping AI-powered edge and semiconductor solutions using Python, Kubernetes, and cloud platforms.
Builds and deploys AI/ML models from prototype to production, focusing on MLOps pipelines, model monitoring, and scalable infrastructure for public-sector and energy clients using PyTorch, TensorFlow, and cloud platforms like AWS SageMaker.
Build and maintain the AI platform, automate ML workload deployments, and engineer secure DevSecOps pipelines using Kubernetes, GitLab, and ML tools.
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