AI Modeling Engineer

Develop modeling and experimentation strategies for high-impact agent problems in voice, language, reasoning, ordering, multilingual behavior, and multimodal understanding.

Build rigorous offline and online evaluations that measure task completion, accuracy, safety, latency, cost, conversational quality, and business outcomes.

Create and maintain representative datasets from simulations, human annotation, production feedback, and difficult edge cases while protecting sensitive data.

Evaluate frontier and open-source models and make clear build, buy, route, prompt, fine-tune, or distill decisions.

Improve prompting, context construction, memory, tool-use policies, structured outputs, model routing, and fallback behavior.

Design fine-tuning, preference optimization, distillation, or other post-training work when it offers a measurable advantage over simpler methods.

Partner with speech and real-time engineers to improve ASR, TTS, turn-taking, interruption handling, pronunciation, multilingual behavior, and end-to-end latency.

Develop analysis tools that explain model failures, slice performance by scenario, detect regressions, and accelerate iteration.

Ship model changes with production guardrails, staged rollouts, monitoring, rollback paths, and clear quality gates.

Translate new research and model releases into concrete product opportunities and communicate tradeoffs to technical and non-technical partners.

Raise scientific and engineering standards through reproducible experiments, thoughtful reviews, and clear documentation.