Senior MLOps Engineer

What You'll Do

• Design, build, and maintain scalable and robust infrastructure for AI/ML (Artificial Intelligence / Machine Learning) systems, including cloud-based environments, containerization, and orchestration platforms
• Develop and implement CI/CD pipelines to automate the deployment, testing, and monitoring of AI/ML models and applications
• Evaluate and integrate new tools, technologies, and frameworks to improve the efficiency and effectiveness of our MLOps processes
• Design and manage Continuous deployment using Kubernetes, ArgoCD, and Jenkins
• Maintain related container registry and model registry.
• Monitor infrastructure utilization and costs pertaining to model training, inference, and GPU utilization
• Monitor and troubleshoot AI/ML systems to ensure high availability, performance, and reliability

What You'll Need

• 4+ years of experience as a DevOps Engineer
• 1 year of previous experience managing AI/ML infrastructure in public cloud environments
• In-depth hands-on experience with at least one public cloud platform, preferably AWS
• Experience with Python or any other programming language
• Experience with Docker and Kubernetes in production
• Experience with Continuous Deployment tools such as Jenkins or ArgoCD
• Experience with Logging and Monitoring tools for SaaS such as Sumo, Splunk, Datadog, etc
• Proficiency in English