Applied ML Researcher (Generative Models)
Job Description
CuspAI is pioneering the use of artificial intelligence to revolutionize the discovery of new materials that will drive human advancement. Our aim is to significantly shorten the time required to develop breakthrough materials from billions of years to just months. We are tackling some of the most pressing global challenges, including energy solutions, clean water accessibility, advancements in computing technology, and carbon capture initiatives. As a vital member of our innovative team, you will have the opportunity to contribute to our mission of redefining the materials landscape through cutting-edge AI research. We are looking for an experienced Applied ML Researcher specializing in generative models to join our expanding team. This role centers on creating state-of-the-art generative models that will enhance our material design processes, enabling the rapid development of next-generation materials essential for sustainability and energy efficiency. You will play a crucial role in ideating and implementing generative models at the atomistic scale, focusing on inorganic crystals, while ensuring these models meet complex physical property conditions. Furthermore, you will integrate your developments into our core platform, contributing to various material discovery campaigns over time.
Key Responsibilities
As an Applied ML Researcher, you will be responsible for developing innovative generative models and integrating them into our material discovery platform. Your work will have a direct impact on shaping the future of materials science.
- Develop and prototype advanced generative models capable of conditioning on multiple target properties.
- Implement, train, and conduct rigorous evaluations of these models against scientific benchmarks.
- Translate theoretical research concepts into functional code.
- Collaborate with engineering teams to ensure model robustness and scalability.
- Run material discovery campaigns utilizing generative tools and analyze their outputs for iterative improvements.
- Collaborate with the materials generation team and computational chemists to align model capabilities with experimental needs.
Required Technical Skills
Soft Skills
Qualifications
- Expertise in machine learning and generative models
- Strong coding skills in Python and frameworks like PyTorch or JAX
- Understanding of material science and chemistry, particularly inorganic crystals
Language Requirements
Programming Languages:
Python, PyTorch, JAX
Spoken Languages:
English, German
Benefits & Perks
- ✓ Competitive salary and equity package
- ✓ 28 days of vacation
- ✓ Professional development budget for conferences and training
- ✓ Work at the forefront of AI-driven scientific discovery
- ✓ Collaborative environment with leading researchers
Working Conditions
Full Time
Company Culture
We foster a diverse and inclusive workplace where collaboration and innovation thrive. Our culture is centered on a shared mission to harness technology for the betterment of the world, and we value diverse perspectives that drive creativity and progress.
Salary Range
Project Types: Not Available
Career Growth: Professional development and training opportunities, Potential for leadership roles in research projects, Collaboration with top-tier researchers in the field