Ship the models that power personalized in-app experiences — predicting what each member is likely to want next based on real-time behavior, family context, and engagement history.
Detect meaningful patterns in product usage data — communication, scheduling, and activity signals — and build the models that turn those patterns into in-app suggestions, alerts, and guidance for families.
AI-native operator. You've made the shift from writing code to orchestrating it. Specs are your primary input mechanism. You trigger agent work, review completed features, and iterate — you're not reviewing individual lines. You measure your own productivity in outcomes shipped and skills contributed, and you can point to concrete examples of features you spec'd and validated rather than typed.
Run the inference serving layer on our own GPU hardware: choose and tune the serving stack (vLLM, SGLang, TensorRT-LLM) for high throughput and low latency.
