MegazoneCloud US

Full-stack Engineer

• Own the design and implementation of production-grade ML pipelines
• Lead architecture and implementation of end-to-end MLOps pipelines, including CI/CD for training, evaluation, approval, and deployment with audit trails
• Design and deploy Terraform infrastructure for ML platform resources
• Build automated Amazon SageMaker training jobs for life sciences workloads
• Implement model performance monitoring and automated retraining triggers
• Establish CI/CD for ML artifacts, including versioning, container builds, integration testing, and staged rollouts with validation gates
• Design model registries and artifact management for governance, reproducibility, and 21 CFR Part 11 compliance
• Implement monitoring, alerting, and auto-scaling for training and inference workloads
• Define and enforce MLOps best practices, coding standards, and architectural patterns
• Serve as overall Tech Lead through architecture reviews, mentoring, and technical decision-making
• Coordinate with customer platform, IT security, and quality teams on networking, security, and compliance

Tech Lead – MLOps, Infrastructure