MLOps Engineer - Remote

Overview

The MLOps Engineer will build and operate scalable, secure infrastructure for Large Language Models (LLMs) at Cognigy, supporting various teams in deploying and maintaining production-grade AI workloads.

In Short

• Design and maintain scalable LLM-serving systems using Kubernetes and KubeRay.
• Automate deployments, rollbacks, and scaling of LLMs.
• Ensure robust monitoring, logging, and alerting for LLM operations.
• Empower ML and product engineers with self-service pipelines.
• Enforce secure deployments and compliance practices.
• Create and maintain technical documentation.
• Evaluate and integrate the latest MLOps technologies.
• Eliminate repetitive tasks to improve operational efficiency.
• Support professional growth and career development.

Requirements

• Experience with MLOps best practices.
• Proficiency in Kubernetes and KubeRay.
• Knowledge of monitoring tools like Prometheus and Grafana.
• Strong understanding of AI infrastructure.
• Ability to automate processes effectively.
• Experience in documentation and knowledge sharing.
• Commitment to security and compliance in deployments.
• Excellent problem-solving skills.
• Ability to work in a collaborative team environment.

Benefits

• Opportunities for career development and training.
• Involvement in high-impact projects.
• Supportive and respectful team culture.
• Access to cutting-edge technologies.
• Commitment to employee growth and success.