MLOps Engineer: Build Scalable ML Pipelines & Cloud Infra

Cognism; Warsaw (KY); On-site; USD 120,000 - 180,000; Full time

Job summary

Cognism is seeking an outstanding MLOps Engineer to join the Data team, reporting to the Engineering Manager. You will optimize ML services, build scalable workflows, and drive reliable deployments across the platform.

You will collaborate with Data Scientists and Engineers to implement best practices, monitor production ML systems, and accelerate the delivery of AI-powered insights for our customers. Excellent English communication and a passion for learning are essential.

Qualifications

• Strong cloud architecture and AWS fundamentals.
• Modern MLOps best practices understanding.
• Machine Learning fundamentals knowledge.
• Data Engineering fundamentals knowledge.
• Infrastructure as Code experience: Terraform, CDK or similar.
• CI/CD pipelines experience: GitHub Actions, CircleCI or similar.
• Cloud networking and security basics.
• Containerization experience: Docker, ECS, Kubernetes or similar.
• Proficient reading and writing Python code.
• Production ML model deployment and monitoring experience.
• Fluent English with strong communication and teamwork skills.
• Enthusiasm for learning modern MLOps solutions.

Responsibilities

• Build and manage automation pipelines to operationalize ML platform.
• Design model training and deployment infrastructure.
• Design and implement secure, reliable, scalable AWS architectures.
• Enforce MLOps best practices across Science and Data teams.
• Bridge AI, Engineering, and DevSecOps for ML deployment.
• Work closely with Data Scientists on tooling and model integration.
• Monitor and maintain production critical ML services.

Skills

Cloud architecture

MLOps practices

Python

CI/CD pipelines

Docker

Kubernetes

Terraform

CDK

GitHub Actions

CircleCI

AWS

Data engineering

Reading/writing Python

Tools

Terraform

CDK

GitHub Actions

CircleCI

AWS

Job description

Cognism is seeking an outstanding MLOps Engineer to join the Data team, reporting to the Engineering Manager. You will optimize ML services, build scalable workflows, and drive reliable deployments across the platform.

You will collaborate with Data Scientists and Engineers to implement best practices, monitor production ML systems, and accelerate the delivery of AI-powered insights for our customers. Excellent English communication and a passion for learning are essential.