CuspAI is a developer of AI-powered materials discovery platforms that use synthesis-aware generative models to design optimized molecular compositions.
ABOUT CUSPAI CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering. We are working on some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the start of what our 'search engine' for next-generation materials will unlock. We invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration. This work matters. Your work matters. We’re on the cusp of the on-demand materials era. Join us. THE ROLE Due to rapid growth in our core AI capabilities, we are seeking an experienced Applied AI/ML Engineer (Agents) to design and build the intelligent agents that power our autonomous materials discovery engine. YOUR IMPACT You will be instrumental in developing the "artificial brain" of our agentic materials discovery engine. This is responsible for orchestrating complex, closed-loop scientific workflows, autonomously making decisions, running simulations, and driving experimental campaigns to find breakthrough materials faster than ever before. Your work will directly accelerate CuspAI’s path to finding solutions for global sustainability challenges. WHAT YOU WILL DO Agentic systems - Design the agentic framework that powers our platform to discover new materials. This includes spanning dynamic, multi-stage simulation workflows from literature-grounded hypothesis generation through to computational and experimental validation - Build the integration that connects agents to ML models, simulation engines, databases, and heterogeneous compute backends - Design pipelines that let agents autonomously plan, schedule, execute, and interpret computational tasks at scale and over long periods of time - Use expert annotations from the Chemistry team to drive targeted improvements in agent planning, retrieval, and decision-making - Create evaluations to measure the effectiveness of agents Experimental design - Build agents that perform experimental design — applying Bayesian optimization, active learning, or related sequential decision-making methods to decide what to compute or measure next, and to balance exploration and exploitation across long-running discovery campaigns - Help close the loop between simulation and physical experiments so that outcomes become durable knowledge — feeding back into what agents know and how their models reason — compounding across campaigns. - Develop strategies for multi-fidelity and multi-objective decision-making, where agents must trade off cost, time, and uncertainty across simulations and physical experiments Interdisciplinary Collaboration - Work closely with Chemists, Materials Scientists, and the rest of the Agent team to co-develop our core orchestration intelligence - Work on customer projects and implement the direct needs required for these projects MUST HAVE SKILLS AND QUALIFICATIONS: - You are someone who gets excited about the opportunity to enable scientists to work on world changing challenges in this domain, with a personal interest in the potential applications of the technology that CuspAI is building. - Proficiency in the modern ML ecosystem such as PyTorch or JAX, with experience taking ML-driven systems from prototype to production - Strong software engineering skills (building systems at scale in a production environment): testing, modular design, CI/CD, and scalable ML operations in production environments - If you have a PhD or Masters degree and 4-5 yrs industry experience this would be ideal, but we will also consider you if you have a PhD and slightly less experience in industry - You have a proactive builder mentality with a bias toward shipping and iteration - Willingness to learn about materials science, and in particular experimental chemistry - to learn the vocabulary of the discipline to meaningfully interact with other stakeholders - Experienced in LLM-assisted programming, knowing its strengths and weaknesses thoroughly. BONUS POINTS (BUT NOT CRITICAL): - Experience applying ML models specifically for materials science, chemistry, or drug discovery applications - Experience with agentic frameworks and building LLM-powered applications - Experience with sequential decision-making methods — Bayesian optimization, active learning, bandits, or reinforcement learning — applied to real-world systems - Advanced agentic-reasoning techniques: planning models, self-improving systems, multi-tool agents, or RLHF/RLAIF workflows ADDITIONAL CONSIDERATIONS This role could be based in our Cambridge, London, Amsterdam or Berlin offices, with the expectation of being in the office three days per week. Additionally, there may be regular travel required to our other offices for collaboration and project oversight. Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world. WHAT WE OFFER - A competitive salary: We value and reward impact and growth - Equity in CuspAI: You have a stake in the success of the company - Time off to stay fresh: 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays - ‘Gold Standard’ parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay - we look after you and your family while we work on the most important materials discovery problems together - Professional development budget: We invest in your career development so you can stay up