TRM Labs - Senior MLOps Engineer, LLMOps

• Write high-quality, maintainable software — primarily in Python, but we value engineering ability over language familiarity. • high-quality, maintainable software • Have a strong background in scalable infrastructure, including: • scalable infrastructure • Containerization and orchestration (e.g. Docker, Kubernetes) • Infrastructure-as-code and deployment (e.g. Terraform, CI/CD pipelines) • Monitoring and logging frameworks (e.g. Datadog, Prometheus, OpenTelemetry) • Understand and implement ML Ops best practices, including: • ML Ops best practices • Model versioning and rollback strategies • Automated evaluation and drift detection • Scalable model and agent serving infrastructure (e.g. vLLM, Triton, BentoML) • Deploy and maintain LLM and agentic workflows in production, including: • LLM and agentic workflows • Monitoring cost, latency, and performance • Capturing traces for analysis and debugging • Optimizing prompt/response flows with real-time data access • Demonstrate strong ownership and pragmatism, balancing infrastructure elegance with iterative delivery and measurable impact. • strong ownership and pragmatism