Senior ML Ops Engineer

📋 Description

• Setup and maintain LLM observability frameworks/tools
• Help improve data annotation tooling
• Ensure stability of LLM calls (rate limits, throughput, backups)
• Help drive security review processes for AI vendors and providers
• LLM cost optimization recommendations (caching, batching, cost drivers)
• Hosting finetuned/open weight ML models

🎯 Requirements

• 5+ years building and operating software systems end-to-end
• Hands-on ML infra: model serving, training pipelines, or LLM integrations
• Strong understanding of cloud infrastructure and distributed systems (primarily AWS)
• Familiarity with observability tooling and cost management for LLM workloads
• Experience with or openness to: Python, Kubernetes, Terraform
• Thrives in a remote-first, async environment: clear communicator, high ownership, low ego