MLOps Engineer - Remote

Overview

The MLOps Engineer will establish and maintain AI/ML infrastructure, ensuring models are efficiently trained, deployed, and monitored. This role focuses on automating ML workflows, optimizing AI operations, and improving model reliability.

In Short

• Implement CI/CD pipelines for model training, testing, and deployment.
• Develop scalable ML infrastructure to ensure reliable AI model performance.
• Automate model retraining, versioning, and monitoring using MLflow, Kubeflow, or Airflow.
• Deploy ML models on cloud platforms (AWS, Azure, GCP) and manage Kubernetes/Docker environments.
• Assist in optimizing data pipelines and integrating AI models with production systems.
• Ensure AI deployments adhere to security, governance, and compliance standards.

Requirements

• Experience with MLOps practices and tools.
• Proficiency in CI/CD for machine learning.
• Strong knowledge of cloud platforms and containerization.
• Experience with data engineering and pipeline optimization.
• Understanding of security and compliance in AI deployments.

Benefits

• Work with a fast-growing SaaS platform.
• Opportunity to innovate in the AI/ML space.
• Collaborate with a talented ML team.
• Flexible working environment.
• Competitive salary and benefits.