Applied AI/ML Engineer (Agents/RL)

About the Company

CuspAI is an AI-first materials discovery company focused on accelerating breakthroughs in next-generation materials. The team brings together highly cited researchers and experienced specialists across AI, chemistry, and engineering to tackle major global challenges such as energy, clean water, future computing, and carbon capture.

The company is building a materials “search engine” designed to unlock discoveries in months instead of years, with the aim of helping create solutions that support human progress and sustainability.

Role Summary

The company is looking for an Applied AI/ML Engineer with a focus on agents and reinforcement learning to help design the intelligent systems behind its autonomous materials discovery platform. This role is centered on building agentic workflows that can plan, execute, evaluate, and improve scientific and computational tasks across long-running discovery campaigns.

The position can be based in Cambridge, London, Amsterdam, or Berlin, and requires in-office presence three days per week. Occasional travel to other offices may also be needed for collaboration and project coordination.

What You’ll Do

• Develop the agent framework that powers materials discovery, including multi-step workflows from literature-based hypothesis generation through simulation and experimental validation.
• Connect agents with machine learning models, simulation tools, databases, and varied compute infrastructure.
• Create orchestration pipelines that allow agents to plan, queue, run, and interpret computational work over extended periods and at scale.
• Use expert feedback from the chemistry team to improve planning, retrieval, and decision-making in the agent system.
• Design and run evaluations to assess how well the agents perform.
• Build agents for experimental decision-making using methods such as Bayesian optimization, active learning, or other sequential decision approaches.
• Support the feedback loop between simulations and physical experiments so that results become reusable knowledge for future reasoning and campaigns.
• Develop multi-fidelity and multi-objective strategies that balance cost, time, and uncertainty across simulations and lab experiments.
• Collaborate closely with chemists, materials scientists, and the broader agent team to co-create core orchestration capabilities.
• Contribute to customer projects by implementing the specific technical requirements needed for those engagements.

Required Profile

• You should be genuinely motivated by the chance to help scientists solve high-impact challenges, with a strong interest in the real-world applications of the technology.
• Strong familiarity with modern ML tools such as PyTorch or JAX, along with experience moving ML systems from prototype stage into production.
• Solid software engineering capability for production-scale systems, including testing, modular architecture, CI/CD, and scalable ML operations.
• An ideal background would be a PhD or Master’s degree plus 4–5 years of industry experience; candidates with a PhD and somewhat less industry experience will also be considered.
• A hands-on, proactive mindset with a strong preference for building, shipping, and iterating quickly.
• Interest in learning materials science and experimental chemistry well enough to collaborate effectively with specialists in those areas.
• Comfort using LLM-assisted programming, including a clear understanding of its advantages and limitations.

Nice to Have

• Experience applying ML to materials science, chemistry, or drug discovery problems.
• Exposure to agent frameworks or LLM-based product development.
• Experience with sequential decision-making techniques such as Bayesian optimization, active learning, bandits, or reinforcement learning in practical systems.
• Familiarity with advanced agent reasoning methods, including planning models, self-improving systems, multi-tool agents, or RLHF/RLAIF-style workflows.

What’s Offered

• A competitive compensation package that reflects impact and growth.
• Equity participation in the company.
• Paid time off of 28 days in Germany, the Netherlands, and the UK, or 21 days in Japan, Singapore, and the US, plus local public holidays.
• Enhanced parental leave: 26 weeks at full pay for primary caregivers and 12 weeks at full pay for secondary caregivers.
• A professional development budget to support ongoing learning and skill growth.
• The chance to work on meaningful sustainability and climate-related challenges using advanced technology.
• A highly collaborative environment spanning AI research, computational chemistry, and experimental science.

Additional Information

CuspAI is an equal opportunity employer and is committed to a diverse, inclusive workplace. Hiring decisions are made without discrimination based on sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital or partnership status, sexual orientation, gender identity, pregnancy or breastfeeding-related condition, veteran status, or any other legally protected characteristic.

Applicants from all backgrounds are encouraged to apply, and the company welcomes the different perspectives that diversity brings. Reasonable adjustments can be provided during or after the interview process where needed.