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Engineer - Data Science
Builds and deploys ML/DL models (classical, deep learning, LLMs) for structured/unstructured data, focusing on MLOps/LLMOps pipelines, model monitoring, and AIOps automation in a telecom/enterprise context.
Training Specialist, Sr. ( Data Scientist , Sr ) 3 PM - 12 AM Shift
Senior Learning Data Scientist building AI-driven analytics, predictive models, and dashboards to optimize training and certification programs using Python, TensorFlow, and Power BI.
Talent Community - MLOps Engineer
Build and maintain scalable ML pipelines and infrastructure for AI-driven projects using Docker, Kubernetes, and cloud platforms like AWS/GCP/Azure.
Senior Machine Learning Engineer
Designs, builds, and deploys production-grade ML systems (LLMs, pipelines, and automation tools) for a mid-market professional services firm’s AI-driven internal workflows, collaborating with data scientists, engineers, and stakeholders.
MLOps Engineer
Build and maintain the infrastructure and pipelines that deploy, monitor, and scale machine-learning models in production, using Docker, Kubernetes, and cloud ML platforms.
Senior AI Solution Architect
Designs and architects enterprise-scale AI solutions, integrating LLMs, RAG, and cloud AI platforms like Azure AI and AWS SageMaker into secure, scalable systems.
0825 - 283(4LAT) | Machine Learning Engineer (On-Site Consultant)
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.
1225 - 405PIC | MLOps Engineer
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.
Software Engineer, Backend (AI Infrastructure)
Build and scale MLOps infrastructure for AI/ML pipelines, including CI/CD, model training/inference, and monitoring to improve AI model deployment velocity.
ENGENHEIRO DE MACHINE LEARNING SR
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.
Senior Site Reliability Engineer - Undersea Dominance
Senior SRE building and operating CI/CD pipelines, Kubernetes clusters, and monitoring for AI-powered maritime defense systems using Terraform, Docker, and cloud platforms.
DevOps Team Lead
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.
Senior AI Platform Engineer
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.
AI Platform Engineer (Cloud)
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.
GCP Data & MLOps Engineer — Remote Cloud Security
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.
GCP Data Engineer & MLOps Specialist
Designs and builds GCP-based data pipelines, AI/ML models, and MLOps workflows using Dataflow, BigQuery, Kubeflow, and Python.
AI Engineer
Build and deploy AI/ML pipelines on GCP and Azure, operationalizing models into scalable IT solutions using Python, SQL, Kubeflow, and BigQuery.
MLOps Engineer
Build and maintain MLOps infrastructure for an AI agent platform, automating model deployment and monitoring for a large commercial bank using cloud tools and Python.
Data Engineer (AI/ML) Contract
Design and deploy AI/ML systems (Generative AI, NLP, vision, recommendations) using Python, TensorFlow/PyTorch, and cloud tools to solve business problems end-to-end.
Expert développeur DevOps/MLOPS
Build and maintain MLOps pipelines and cloud infrastructure to deploy AI models end-to-end, using Python, Docker, Kubernetes, Azure ML, and CI/CD.