Reflection - Research Program Manager

• Build the foundational infrastructure for model evals and safety at Reflection. Define the evaluation frameworks, tooling requirements, and operational processes that will underpin how we assess model capabilities, risks, and readiness for release. • Stand up model safety operations as a function, including establishing the workflows, review cadences, and decision frameworks that connect safety evaluation to the model development and release lifecycle. • Partner with research and engineering leads across pre-training, mid-training, and post-training to embed safety and evaluation checkpoints into the development process in a way that is rigorous without being a bottleneck. • Drive the scoping and prioritization of eval science and eval infrastructure investments, working with technical leads to determine what to build in-house, what to adopt, and where to invest research effort. • Establish Reflection's engagement with the external safety ecosystem, including third-party assessments, academic partnerships, and industry safety frameworks. Represent the company's safety posture to external stakeholders with credibility and clarity. • Create visibility and reporting structures that give leadership a clear, honest picture of model safety status, evaluation coverage, and open risks, so they can make informed decisions at the pace the business requires. • Champion a culture of blameless post-mortems and continuous learning, turning every safety-relevant finding into a concrete improvement to our systems and processes. • 7+ years of experience in technical program management, research operations, or ML engineering, with demonstrated experience standing up new functions, teams, or programs from scratch. • Familiar with the landscape of model evaluation and AI safety, including evaluation methodologies, red-teaming, alignment research, and the evolving regulatory and industry safety ecosystem. You don't need to be a safety researcher, but you need to understand the space well enough to make sound judgments about what matters and what to prioritize. • Deep enough technically to engage with researchers and engineers on topics like model behavior, evaluation design, data pipelines, and safety-critical system architecture. You follow the technical thread and you know when something doesn't add up. • Proven ability to build structures where none exists. You've taken ambiguous mandates and turned them into functioning programs with clear ownership, measurable outcomes, and durable processes. • Strong stakeholder management skills spanning deeply technical ICs, research leadership, and external partners. You build trust through competence and follow-through. • Excited to build from zero to one. We are a small, fast-moving team and this role will help define how model safety and evaluation works at Reflection. • Motivated by enabling researchers and engineers to build the world's most capable open-weight AI systems, responsibly.