Applied ML Researcher (Generative Models) in Cambridge

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 harness 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.

Due to growth, we are seeking an experienced Applied ML Researcher (Generative Models) to join our team and build state‑of‑the‑art generative models to design new materials at CuspAI.

Your Impact

• Build novel generative models that accelerate the discovery of next‑generation materials for energy and sustainability challenges.
• Initially focus on ideating and implementing generative models for inorganic crystals at the atomistic scale; condition these models on complex target properties, and integrate them into our core platform.
• Over time, expand to other material classes, length/method scales, and end‑to‑end discovery campaigns.

What You Will Do

• Develop and prototype new ideas for generative models of material candidates conditioned on multiple target properties, focusing on inorganic crystals.
• Implement, train, and rigorously evaluate these models against scientific benchmarks.
• Translate theoretical concepts from research papers into functional, high‑performance code.
• Integrate models into the wider CuspAI platform, ensuring robustness, scalability, and accessibility for discovery workflows.
• Collaborate with software engineering to adhere to best practices in coding, testing, and deployment.
• Run material discovery campaigns using generative tools to identify promising candidates for real‑world applications such as carbon capture or battery materials.
• Analyze campaign outputs to iteratively improve model performance and domain relevance.
• Work with the material generation team and wider technical team to align capabilities with experimental realities, partnering with computational chemists for constraints.

Must Have Skills and Qualifications

• Deep experience designing, building and training generative ML models (diffusion, flow models, VAEs).
• Proficient Python coding with PyTorch or JAX, moving quickly from idea to prototype to integrated solution.
• Collaborative spirit, communicating complex technical concepts across scientific backgrounds.
• Enthusiasm for using technology to address sustainability challenges.

Bonus Points (Not Critical)

• Domain expertise in chemistry or material science, especially inorganic crystals and structural properties.
• Experience training and evaluating ML models at scale.
• Relevant publications in ML, chemistry, or material science.
• Willingness to work from Amsterdam for this team.

Additional Considerations

Role may be based in Amsterdam, Berlin, Cambridge or London, with an expectation of being in the office three days per week and regular travel for collaboration.

What We Offer

• Competitive salary plus equity package.
• 28 days holiday.
• Professional development budget for conferences and technical training.
• Opportunity to work at the forefront of AI‑driven scientific discovery with world‑class researchers.
• Direct impact on advancing materials science through cutting‑edge technology.
• Collaborative environment bridging AI research, computational chemistry, and experimental science.

Equal Opportunity

CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace. We do not discriminate based on 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. If you require any specific adjustments during or after the interview process, we will accommodate within reason.

Join Us

Shape the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world.