AI/ML Platform Engineer - Brazil (Remote)

AI/ML Platform Engineer Location: Brazil Employment Type: Contract Work Model: Remote Role Overview We are seeking an experienced AI/ML Platform Engineer to design, build, and maintain scalable AI/ML infrastructure and delivery platforms. The ideal candidate will have hands-on experience supporting GPU workloads, LLM integrations, Kubernetes, Docker, Helm, AWS, Terraform/Ansible, CI/CD, and DevOps tooling. Key Responsibilities • Design and engineer scalable infrastructure for AI/ML workloads and GPU-based environments. • Build and maintain platforms supporting LLM applications and integrations. • Deploy and manage AI/ML workloads using Kubernetes, Docker, and Helm. • Develop and maintain CI/CD pipelines for ML models, applications, and infrastructure. • Automate infrastructure provisioning and configuration using Terraform and Ansible. • Deploy and manage AI/ML infrastructure on AWS. • Implement monitoring, logging, security, and performance optimization for AI/ML platforms. • Support model deployment, integration, scaling, and operationalization. • Troubleshoot infrastructure, container, Kubernetes, and deployment issues. • Establish DevOps and MLOps best practices for reliable AI/ML delivery. • Collaborate with data scientists, ML engineers, software engineers, and DevOps teams. Required Skills • Strong experience as an AI/ML Platform Engineer, MLOps Engineer, or DevOps Engineer supporting AI/ML platforms. • Hands-on experience with: • Kubernetes • Docker • Helm • AWS • Terraform and/or Ansible • CI/CD • GPU workloads • LLM integrations • Strong understanding of cloud infrastructure, containers, orchestration, and automation. • Experience building scalable and highly available AI/ML platforms. • Strong scripting and automation skills. • Knowledge of monitoring, logging, security, and infrastructure optimization. Preferred Skills • Experience with MLOps platforms and practices. • Experience with NVIDIA GPU infrastructure and CUDA environments. • Knowledge of Python and AI/ML frameworks. • Experience with LLM platforms, model serving, and inference workloads. • Familiarity with AWS services such as EKS, EC2, S3, and SageMaker. • Experience with Prometheus, Grafana, or similar observability tools.