Senior MLOps Engineer: Build Scalable AI Pipelines

Talanto; Poland; Hybrid; PLN 234,000 - 352,000; Full time

Job summary

Talanto is seeking a Senior MLOps Engineer – AI Infrastructure & Pipelines in a Poland-based hybrid role to automate ML lifecycles, build scalable data pipelines, and deploy robust AI systems in production.

You will collaborate with data scientists and engineers to ensure reproducibility, monitor models, and secure AI workflows while applying best practices in security and governance across the pipelines.

Qualifications

• Minimum 4 years of experience in MLOps, AI infrastructure, or related engineering fields.
• Strong Python skills and scripting (bash).
• Hands-on CI/CD experience with Jenkins or GitLab CI/CD.
• Experience with Docker and Kubernetes in production.
• Experience on AWS/Azure/GCP for ML data pipelines.
• Familiarity with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Knowledge of data pipelines, ETL, and orchestration tools.

Responsibilities

• Design and maintain CI/CD pipelines for ML models.
• Automate deployment, testing, and monitoring of AI solutions.
• Manage cloud infrastructure for ML workloads (AWS/Azure/GCP).
• Collaborate with data scientists to ensure reproducibility and scalability.
• Implement model monitoring with MLflow, Prometheus, or Grafana.
• Troubleshoot production issues to maintain uptime.
• Document workflows and infrastructure configurations clearly.
• Apply security, compliance, and data governance best practices.
• Support improvements of MLOps tools and processes.
• Stay updated on AI infrastructure trends and practices.

Skills

Python

Bash scripting

CI/CD pipelines

Docker

Kubernetes

Cloud platforms

ML frameworks

Data pipelines

Observability

English communication

Tools

Jenkins

GitLab CI/CD

MLflow

Prometheus

Grafana

Job description

Talanto is seeking a Senior MLOps Engineer – AI Infrastructure & Pipelines in a Poland-based hybrid role to automate ML lifecycles, build scalable data pipelines, and deploy robust AI systems in production.

You will collaborate with data scientists and engineers to ensure reproducibility, monitor models, and secure AI workflows while applying best practices in security and governance across the pipelines.