Technical Program Manager (Model Alignment and Deployment)

Join as a Technical Program Manager for Model Alignment and Deployment. In this critical role, you will connect cross-functional teams, drive clarity and execution, and ensure the successful delivery of powerful pretrained language models. You will work closely with research engineers, safety experts, data scientists, infrastructure engineers, and UX researchers to turn ambitious model development goals into well-scoped, well-tracked programs. This position requires strong communication skills, proficiency in SQL and Python, and a deep familiarity with post-training and alignment concepts. - Lead planning and execution of cross-functional programs spanning data collection, annotation pipelines, alignment workflows, safety guardrails, and model serving. - Serve as the connective tissue between Post-Training, Safety Engineering, Trust & Safety, ML Infra, UXR, and Product, translating model development, safety, and user experience priorities into executable roadmaps. - Drive visibility into data pipeline health, annotation quality, training run progress, and deployment readiness, identifying bottlenecks across teams and leading efforts to improve tooling, process, and developer velocity. - Exceptional communication skills - able to translate deep technical work into clear narratives for leadership, and to hold detailed technical conversations with engineers across different disciplines - Proficiency in SQL and Python - 5+ years of experience in technical program management, research operations, or product execution in a fast-moving AI, ML, or research environment - BS in a quantitative, scientific, or technical field; MS or PhD a plus - Obsessive about data integrity, operational rigor, and process quality without letting process slow teams down - Deep familiarity with post-training and alignment concepts (supervised fine-tuning, RLHF, AI safety frameworks, LLM evaluation) as well as model deployment/serving, sufficient to engage substantively with both research and infrastructure engineers - Strong analytical mindset; comfortable working with data and user insights to measure program health, identify trends, and drive decisions - Proven ability to lead complex, multi-team programs in ambiguous, rapidly evolving environments; track record of shipping with quality and speed - Hands-on experience with data pipelines, annotation platforms, ML evaluation tooling, or human-in-the-loop workflows - Experience managing annotation vendors or external data partners - Familiarity with distributed training, experiment tracking, or ML infrastructure (Kubernetes, Docker, cloud) and model serving systems - Prior experience embedded in an AI research team, foundation model lab, or Trust & Safety engineering team - Direct experience managing AI safety, trust, quality eval, or red-teaming programs