• You will design and implement scalable APIs/services for developing AI agents, including orchestration, memory, tool use, and learner interaction • You will implement rigorous evaluation frameworks to improve agent performance (offline and in-product), and build the instrumentation to make results actionable improvement cycles • You will build data flows/pipelines that allow real-time personalization and learning insights • You will ensure data quality and accessibility for training and evaluating learning agents • You will improve developer velocity with solid API design, testing practices, and realistic architecture choices • You will ship end-to-end product slices: implement backend capabilities and the corresponding lightweight web UI (and occasionally mobile) to unblock product progress • You will build lightweight internal tools/admin surfaces for evaluation, debugging, content/ops workflows, and product iteration • You will collaborate with product/design to deliver high-quality user experiences while keeping scope and maintainability sane • You will help establish the basics of production readiness: monitoring, dashboards, logging/tracing, and performance/cost hygiene • You will contribute to automated testing and deployment pipelines for rapid, safe iteration (CI/CD, rollbacks, environment hygiene) • You will participate in incident response when needed and help shape runbooks, postmortems, and an on-call model appropriate for our current stage

• You will design and implement scalable APIs for agent orchestration and learner interaction • You will build data pipelines that feed agent evaluation and continuous improvement cycles • You will create event streaming infrastructure for real-time learner interaction analysis • You will ensure data quality and accessibility for training and evaluating learning agents • You will improve data infrastructure for cost and performance in close coordination with Data and ML teams • Design and implement rigorous evaluation frameworks to measure agent performance and improve cycles • Develop LLM evaluation processes and perform error analysis to identify systemic improvements for agentic learning systems • Support instrumentation that makes evaluation relevant (metrics, traces/logs, and analysis workflows) • Participate in on-call rotation and incident response for learning platform reliability • Contribute to runbooks, postmortems, and reliability improvements as we evolve our operating model

• We're building the world's first viral agent. An AI purpose built for influencer marketing. • An autonomous agent that goes from "I need this campaign to break" to "50 influencers live next week" with minimal human intervention. • We have proprietary data on thousands of influencers and what makes content go viral, plus direct relationships with the influencers themselves. • We're offering significant equity to people who want to build something that matters.

• Design, adapt, and implement machine learning and classical algorithms from proof of concept (POC) to working prototypes. • Plan and conduct experiments to address critical business questions. • Develop and maintain model testing and statistical verification processes. • Implement data processing and training pipelines. • Extend existing machine learning and deep learning codebases and frameworks. • Thoroughly document POCs and experiments. • Plan and lead long-term research activities. • Assist in recruiting talent in the field. • Stay up-to-date with the latest developments in AI and machine learning.