We are seeking a skilled MLOps & Agentic Platform Engineer. This role involves managing model registries, developing continuous training loops, and implementing A/B testing infrastructure. The ideal candidate will have a strong DevOps/MLOps background and be adept at deploying scalable microservices and building observability dashboards. Responsibilities: Manage model registries, continuous training loops, and A/B testing infrastructure. Deploy agents as scalable microservices on Kubernetes. Build observability dashboards to track token usage, latency, and agent reasoning paths. Qualifications: Strong DevOps/MLOps background (Kubernetes, Docker, Terraform). Experience with MLflow, Weights & Biases, or LangSmith. Knowledge of building scalable microservice architectures.
