Machine Learning Engineer

• Own and manage the full lifecycle of both ML models and core infrastructure – from development and deployment to monitoring and continuous improvement.
• Build and maintain robust CI/CD pipelines for both software and ML workflows.
• Ensure reliability, scalability, observability, and security of production systems and ML infrastructure.
• Automate deployment, orchestration, and environment management using modern DevOps tooling.
• Collaborate closely with software engineers, ML engineers, and product teams to bring ML-powered features to production.
• Proactively detect, troubleshoot, and resolve infrastructure and model performance issues.
• Stay up to date with industry best practices in DevOps, MLOps, and infrastructure engineering.
• Document infrastructure, workflows, and operational procedures clearly and thoroughly.

MLOps Engineer

MLOps & AI Infrastructure Leadership