Senior Machine Learning Engineer

Design and implement scalable ML infrastructure using Ray to support model training, deployment, and inference at scale.
Leverage Kubernetes to orchestrate containerized applications and manage ML models and services.
Develop and maintain CI/CD pipelines for automated testing, deployment, and lifecycle management of ML applications and infrastructure.
Implement robust monitoring, logging, and alerting to ensure high availability, performance, and security of the ML platform.
Collaborate with data scientists and ML engineers to optimize data pipelines and model performance, incorporating customer feedback to refine models.
Provide DevOps/SRE support, incident response, performance tuning, disaster recovery planning, and advocate for growth-minded, customer-focused practices.