Postdoctoral Researcher (Foundational AI: Intelligent Systems)

Conduct original research in one or more areas: memory; reasoning and control; tools and computation; or relevant multi-agent algorithms and architectures. Formulate falsifiable hypotheses and evaluate them using controlled experiments, matched baselines, ablations, held-out tasks, and reproducible research artifacts. Contribute to the team's task environments, evaluation harnesses, traces, or other reusable infrastructure as appropriate. Investigate reliability, cost, latency, provenance, authorization, privacy, and human-oversight constraints alongside capability. Pursue an independent research program and contribute to the team's broader scientific direction. Disseminate research through peer-reviewed publications, conference presentations, open scientific engagement, and collaboration with the broader research community. A PhD (completed or near completion) in Machine Learning, Computer Science, Mathematics, Statistics, or a related field. Expertise in one or more sub-fields of AI/ML, evidenced by top-tier publications and/or experience. A strong record of original, peer-reviewed research published at leading venues in AI, machine learning, such as NeurIPS, ICML, ICLR, UAI, AISTATS. Research evidence in persistent memory, long-horizon planning, adaptive computation, formal or practical tool interfaces, verification, recovery, or agent evaluation. Experience with reproducible benchmarks, evaluation harnesses, systems instrumentation, security, privacy, or safety research for AI agents. Excellent written and verbal communication skills, with the ability to explain complex ideas to a broad scientific audience.