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.