MLOps Engineer

About the role

We are looking for a skilled MLOps Engineer to bridge the gap between our Data Science and Infrastructure teams. You will support MLOps tasks, create CI/CD pipelines, provision cloud resources, and orchestrate Kubernetes deployments.

Key responsibilities

• Design, implement, and maintain scalable MLOps pipelines on AWS using SageMaker, EC2, EKS, S3, Lambda and related services.
• Troubleshoot and manage Kubernetes (EKS) clusters for model and microservice deployment.
• Develop and maintain CI/CD pipelines for model and application deployment, testing, and monitoring.
• Collaborate with Data Science and DevOps teams to streamline the model development lifecycle from experimentation to production.
• Implement security best practices, including network security, data encryption, and role‑based access controls.
• Monitor, troubleshoot, and optimize data and ML pipelines for high availability and performance.
• Set up and manage model monitoring systems for performance drift.

Required profile

• Bachelor’s degree in Computer Science, Engineering or related field.
• 2+ years of hands‑on experience in MLOps, DevOps or related areas.
• Strong problem‑solving and communication skills.

Required skills

• AWS services (SageMaker, EC2, EKS, S3, Lambda)
• Kubernetes and Docker
• Infrastructure‑as‑code tools (Terraform, CloudFormation)
• CI/CD tools (GitLab CI)
• Monitoring and logging (Prometheus, Grafana, CloudWatch, ELK Stack)
• Python and Bash scripting
• Linux environment proficiency

What we offer

• Attractive remuneration package plus performance‑related reward
• Private health insurance
• Corporate pension fund
• Intellectually stimulating work environment
• Continuous personal development and international training opportunities