About the RoleJoin micro1 to bridge cutting-edge AI research with real enterprise impact. As MTS, Enterprise AI you’ll turn messy business operations into clean research problems and data. Your expertise in Research signal judgment, ML-oriented data design, and Ops-to-research translation will shape how AI agents work inside Fortune 500 workflows.What You’ll DoResearch signal judgment: Apply Research signal judgment to decide what problems are worth solving and what data will actually move model performanceML-oriented data design: Architect ML-oriented data design for enterprise use cases: workflows, documents, tickets, and multi-step processesOps-to-research translation: Lead Ops-to-research translation by converting real business operations into evals, datasets, and RL environments+1: Leverage +1 additional skill such as product strategy, stakeholder management, or ML systemsPartner with enterprise teams to map operations → AI tasks → training dataDesign evals and benchmarks that measure business outcomes, not just accuracyBuild data pipelines that capture quality signal from enterprise tools and humansCollaborate with research engineers and scientists to ship agents into productionRequired SkillsProven Research signal judgment: ability to spot high-leverage problems in ambiguous settingsExperience with ML-oriented data design for LLMs, agents, or enterprise MLTrack record of Ops-to-research translation: turning operations into researchable problems+1 skill: Python, LLMs, product thinking, or technical program leadershipStrong communication with both executives and research teams🌈 Preferred QualificationsBackground in consulting, product, or ML engineering at enterprise scaleExperience deploying AI in SaaS, finance, healthcare, or ops-heavy industriesFamiliarity with RLHF, tool-use agents, and evaluation frameworksMS/PhD in CS, ML, or MBA with technical depth💰 Compensation & BenefitsPay: $250,000 – $500,000/year based on experience and impactEquity + comprehensive benefitsFlexible hoursRemote1 opening availableBe the bridge between research and billion-dollar enterprise problems