Lead Machine Learning / MLOps Engineer

Responsibilities

• Model Development & Production
• Develop, fine-tune, and deploy machine learning and foundation models into robust production environments
• MLOps & Pipeline Engineering
• Build, scale, and operate end-to-end MLOps pipelines, including CI/CD for ML, model lifecycle management, monitoring, and observability
• Cloud & Infrastructure Management: Deploy and manage ML workloads on Azure and Kubernetes (AKS), ensuring high availability, scalability, and security
• Performance Optimization
• Manage multi-GPU-based workloads and optimize model performance, latency, and resource utilization
• Software Engineering Excellence: Uphold rigorous software engineering standards, including automated testing, high code quality, CI/CD pipelines, and infrastructure as code
• Cross-Functional Collaboration
• Partner closely with ML researchers, data scientists, and engineering teams to translate research breakthroughs into production-ready systems

Languages