AI System Engineer

Experience in ML systems or applied AI, particularly in LLMs, ASR, or TTS pipelines. Strong background in real-time or streaming systems and concurrent architectures. Proven ability to productionize AI models, serving, scaling, and monitoring them. Proficiency in Python. Experience deploying systems on Kubernetes or similar orchestration frameworks. Familiarity with TypeScript for frontend or orchestration logic. Comfort with automated testing, metrics, and observability as part of core development practice.

Design and build real-time multimodal pipelines connecting ASR, LLMs, TTS, and avatar rendering. Develop the observability layer for the pipeline (metrics, tracing, performance instrumentation). Build infrastructure management tools to deploy, version, and scale models. Develop automated tests and evaluation frameworks for reliability, synchronization, and quality. Integrate and optimize the full system for low latency, high reliability, and graceful degradation. Collaborate with product and AI teams to enable Superhumans for presentations, media, information sharing, and knowledge base training.