Applied AI/ML Engineer (Agents/RL) in Cambridge

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/RL) 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

• Existing systems
  • Find the best ways to use existing LLMs and sub agents to generate and use data in our platform
  • Make improvements based on labelling provided by Chemistry team
  • Create a framework to evaluate effectiveness of agents
• New systems
  • Design and build tool‑using agents that discover new materials
  • Implement workflows in the CuspAI platform that involve agentic search
• Experimental design
  • Build agents that can perform experimental design (e.g. Bayesian Optimization)
  • Integrate experimental design agent(s) with computational components of the platforms
  • Combine systems and experimental design elements (computational and experimental actions) into one agentic workflow
• Interdisciplinary Collaboration
  • Work closely with Chemists, Materials Scientists, and the rest of the Agent team to co‑develop our core orchestration intelligence

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.
• Strong software engineering skills (building systems at scale in a production environment)
• If you have a 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
• Experience with reinforcement learning (designed and implemented reinforcement learning algorithms)
• 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

Bonus Points (But Not Critical):

• Experience applying ML or RL models specifically for materials science, chemistry, or drug discovery applications
• Experience with agentic frameworks and building LLM‑powered applications
• Deep knowledge of transformer architectures and experience with prompt engineering for complex, multi‑step tasks

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.

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 to date with the latest industry knowledge or add to your skills to increase impact and growth
• Solve meaningful problems: See how your work has a direct impact on advancing materials science and solving sustainability and climate‑related problems through the creation and application of bleeding‑edge SOTA technology and revolutionary techniques
• True interdisciplinary teamwork: Be part of a deeply collaborative environment bridging AI research, computational chemistry, and experimental science – work with world‑class researchers and engineers who enjoy sharing knowledge and supporting each other

Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world. CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace. We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law. We actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team. Please let us know If you require any specific adjustments during or after the interview process. We will do everything we can within reason to accommodate.