SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Periodic Labs is an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs in materials, energy, and related domains. This Business Operations role sits at the intersection of frontier AI research and physical science, serving as the connective tissue between research teams, model development roadmaps, and broader strategic needs.
You will operate in a deeply technical environment without being a researcher yourself, supporting the operating rhythm of the research organization through research planning cycles, milestone tracking, experiment prioritization, and cross-team coordination between AI and physical sciences. Key responsibilities include designing systems that give leadership real-time visibility into research progress and resource utilization; partnering with research leadership to translate long-horizon scientific goals into quarterly operating plans and hiring priorities; identifying and removing organizational, process, and tooling bottlenecks; and coordinating compute, lab equipment, and infrastructure allocation across projects.
You will serve as the operational link between research outputs and product development, ensuring scientific milestones translate into clear product implications. You'll drive the product planning process in partnership with founders and product leads, building scalable processes and artifacts (roadmaps, decision logs, spec templates, review cadences) as the company grows. Additional responsibilities include leading evaluation design and benchmark development, supporting special projects and strategic analyses, and managing external partnerships at the research-commercial boundary.
Ideal candidates hold an undergraduate or graduate degree in physics, chemistry, materials science, or a closely related quantitative discipline, with 4+ years of experience in strategy, operations, product management, or chief-of-staff roles—preferably in technical, research-driven, or AI organizations. You should be able to read and engage with primary scientific literature, follow technical discussions at the frontier, and translate insights into operational decisions. Exceptional analytical thinking, structured problem-solving, and outstanding communication skills are essential. You'll need high agency, strong judgment, and the credibility to influence across teams of world-class researchers and engineers. Experience designing planning and prioritization systems in exploratory, high-stakes environments is valuable. A PhD in physical science or engineering with research experience at the computation-experiment boundary, prior research operations or technical program management experience, hands-on AI/ML workflow knowledge, or a background spanning both scientific and commercial sides of technology organizations would strengthen candidacy.
