Location: Full remote Job Type: Full-time About the Role: From 5411Hub, we are looking for a Senior Machine Learning Engineer with solid experience in MLOps to develop and implement end-to-end machine learning systems — from training pipelines to inference services in production. You’ll collaborate with data scientists and software engineers to ensure scalable, efficient, and production-ready solutions. This role combines robust engineering, flow automation, and a culture of shared ownership within a challenging and global technical environment. 🔧 Key Responsibilities Design, build, and maintain automated MLOps systems. Implement training pipelines and inference services in production. Integrate models into production environments alongside data scientists and software engineers. Ensure best practices in model versioning, monitoring, and deployment. Participate in on-call rotations to guarantee service availability and resilience. ✅ Requirements Experience with containerization and microservices (Docker or similar). Expertise in pipeline automation, CI/CD integration, and model monitoring. Knowledge of model serving tools (TensorFlow Serving, TorchServe). Strong Python skills and experience with data science frameworks (NumPy, pandas, PyTorch, TensorFlow). Experience with AWS (EC2, S3, EKS) and tools like Kubeflow Pipelines, MLflow, FastAPI. Practical knowledge of Apache Spark and job optimization. Solid engineering practices: version control, testing, code review. Advanced English and excellent collaborative communication skills. 💡 Nice to Have Foundations in Kubernetes (pod deployment, resource management). Experience developing APIs with FastAPI. Knowledge of Terraform for infrastructure automation.