Cloud Platform Lead Engineer, ML DevOps

- Lead the design, development, and maintenance of cloud infrastructure for ML experimentation, training, and production deployments. - Define the technical direction and best practices for ML platforms, MLOps, reliability, and cloud infrastructure. - Architect ML platforms for high availability, fault tolerance, and resiliency across various environments. - Establish and manage observability standards, including metrics, logging, tracing, alerting, and SLOs for ML platforms. - Build and oversee CI/CD pipelines and automate infrastructure and ML workflows. - Drive infrastructure-as-code, automation, and reliability standards throughout the platform. - Proactively monitor, troubleshoot, and enhance platform availability, performance, scalability, and recovery. - Advocate for MLOps best practices, including model versioning, validation, promotion, monitoring, and rollback strategies. - Ensure platform security, compliance, and cost efficiency. - Collaborate with data scientists, ML engineers, and product teams to deliver reliable, self-service ML capabilities. - Mentor engineers through design discussions, code reviews, and hands-on technical guidance. - Contribute to roadmap planning, prioritization, and execution aligned with business and client needs. - Engage in agile ceremonies and drive continuous improvement within the team.