Applied AI​/ML Engineer; Property Prediction Foundational Models

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.

Due to the rapid scaling of our scientific intelligence and data curation capabilities, we are seeking an Applied AI/ML Engineer to build and apply multi-modal foundation models to solve a broad range of materials discovery tasks.

* Note that you would be joining as a ‘Member of Technical Staff’, but the indicative job title above hopefully helps to explain the nature of this role.
Hiring timelines: We’re aiming to start interviewing for this role in mid-January and would like to make an offer by mid-February.

You will be building and refining the property prediction and material characterization models that accelerate the discovery of world-changing molecules.
You will be joining a world-class team, where your work will bridge the gap between frontier AI research and production-grade scientific applications.
Your initial focus will be on owning the development and integration of property prediction models and applying them to existing and future project workflows. Over time you will play a key role in evolving our multi-modal foundation models to handle increasingly complex scientific modalities.

Model Development & Application

• Own the development, integration, and evaluation of property prediction models within customer workflows, ensuring reliable deployment and performance.
• Adapt and fine-tune our core foundation models for specific property prediction applications to meet high-stakes scientific requirements.
• Contribute to the ongoing development of multi-modal foundation models for molecular systems, designing architectures that handle diverse input and output modalities.
• Implement uncertainty quantification methods to support Bayesian optimization pipelines, helping scientists navigate the vast space of potential materials.

Engineering Excellence

• Build robust learned representations that generalize across various downstream tasks.
• Apply strong software engineering best practices to ensure all systems are scalable, reliable, and maintainable.
• Support the deployment and integration of production-grade foundation models into our core platform.

Scientific Collaboration & Integration

• Partner closely with our internal Chemists and Materials Scientists to integrate computational and experimental workflows into one seamless optimization loop.
• Proactively learn the technical vocabulary of materials science and experimental chemistry to facilitate deep, meaningful interactions with domain experts.
• Contribute to our mission by ensuring all system designs align with CuspAI's commitment to sustainability and solving the world’s most pressing physical challenges.

• Strong software engineering skills and a proven track record of building complex systems in a production or industrial environment.
• Significant experience building, training, and evaluating relevant ML models (e.g. Graph Neural Networks, Transformers, or Generative Models).
• Educational background (Master’s degree or PhD) in Computer Science, Machine Learning, or a related quantitative field.
• For candidates without a PhD, 4-5 years of industry experience in an ML or Software Engineering role is highly preferred.
• A deep interest in the connection between AI and…