Job Description

Own RAG pipelines and agentic workflows (end-to-end accuracy); GPU-optimized model deployment (Trident-style architecture); Production MLOps including distillation, fine-tuning, and training orchestration; Data modeling for AI persona capabilities; Infrastructure responsibilities including Docker, CI/CD, logging, monitoring, and observability. Requirements: 3-12 years shipping AI/ML in production (notebooks do not count); startup or scale-up experience where you owned what you built; strong Python; bonus for C++/Java/C# in performance-critical paths; Hands-on with RAG, MLOps tooling, and GPU deployment at scale. W2 full-time. Must be authorized to work in the US. No remote.