Research Engineer, Post-Training

📋 Description Drive post-training experiments to improve agent performance within cost, latency, and governance. Optimize agent harnesses, including domain-specific skills and retrieval strategies. Design and develop grading and reward systems for high-stakes legal work. Study agent behavior and convert findings into training data or harness changes. Collaborate with researchers and external partners to drive concrete model improvements. 🎯 Requirements Hands-on post-training or model-training experience (SFT, RLHF, RLAIF). Strong judgment of model behavior; read traces and identify failure modes. Strong Python and research-engineering ability; write code and debug experiments. Ability to self-manage ambiguous applied research and communicate clearly with teams. 🎁 Benefits Hybrid work model with collaboration across teams. Opportunity to work on a rapidly growing company with global impact. Global customer base across 70+ countries. Equal opportunity employer; accommodations available.