Strategic Projects Lead

Founding Strategic Project LeadSalary: $180k - $225k base + Founding Employee Equity + bonusLocation: New York City (preferred, flexible for the right candidate)Morpheus are partnered with a VC-backed startup building the evaluation and training infrastructure for autonomous healthcare AI. They create high-fidelity RL training gyms and environments that improve frontier models and agents on real clinical, operational, and administrative workflows, using long-horizon evaluations, expert feedback, verifier-driven tasks, RL environment design, and real-world healthcare data. The business is commercially live, connected with frontier labs, and hiring to meet immediate delivery needs.They are looking for an exceptional Founding Strategic Project Lead to own lab-facing delivery and expansion across existing frontier lab relationships, turning early engagements into shipped RL environments, gym artifacts, and post-training datasets that convert into larger contracts. This role suits someone with extremely high agency who has shipped complex technical projects directly to frontier labs, understands RL environment design and post-training data pipelines, and can operate under ambiguity in a small, fast-moving startup while holding a high quality bar.What You'll Do:Own end-to-end execution across lab engagements: scoping, timelines, milestones, risks, and delivery of RL environments and post-training data artifactsBe customer-facing with frontier lab stakeholders: run cadence, align on RL environment specs and acceptance criteria, and communicate progress clearlyTranslate ambiguous lab asks into concrete workstreams: RL environment/gym spec, reward and verifier design, task library plan, QC plan, and delivery roadmapDrive "quick-hit" pilots: deliver small, high-quality sample RL environments or post-training data slices early to prove fit and de-risk full deliveryCoordinate cross-functionally across ML/RL researchers, environment engineers, and clinicians/domain experts to ship complex, multi-step projects on time and at frontier-lab qualityBuild and enforce delivery quality systems for RL environments and datasets: definition-of-done checklists, verifier/reward QC gates, auditability, versioning, and postmortemsHelp convert successful deliveries into expanded scopes and longer-term contracts with frontier labsWhat They're Looking For:Demonstrated experience delivering complex technical projects directly to frontier AI labs (as a vendor, partner, or embedded team), ideally involving RL environments, evals, or post-training deliverablesWorking understanding of RL environments: reward design, verifiers, environment/task construction, and how these feed into model training and evaluationHands-on familiarity with post-training data pipelines: data/annotation workflows, RLHF/RLAIF-style processes, or similarExceptional ability to turn ambiguity into structure: clear goals, tight scope, crisp milestones, and measurable success criteria on multi-workstream projectsStrong written communication, producing specs, updates, and summaries that reduce confusion and accelerate decisions with technical stakeholdersHigh agency and comfort operating in a small startup with limited process, resources, or precedent to lean onAbility to work with technical teams (RL/ML researchers, engineers) and domain experts while making high-judgment tradeoffs on scope, quality, and timelinesExperience in regulated domains (healthcare, fintech, security) where QA/QC and auditability matter is a plusExperience converting early customer demand into expanded contractsWhy JoinThis is a chance to sit at the center of one of the most important bottlenecks in AI: making autonomous agents reliable in real world, high-stakes domains through better RL environments and post-training data. You'll help translate frontier lab demand into shipped artifacts that directly improve model performance, and build the delivery engine that lets the business scale.Open to exceptional candidates across a range of seniority levels.