Lila Sciences is the worldâs first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method. We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before.
Requirements
- Strong programming skills in Python with deep expertise in LLM frameworks (PyTorch, HuggingFace Transformers, LangChain, LlamaIndex, and related toolkits).
- Expertise in LLM reasoning methods: in-context learning, test-time compute, chain-of-thought, or tool-augmented reasoning.
- Ability to balance theoretical research with practical ML engineering to deliver scalable solutions.
- Research experience in causal reasoning, symbolic AI, or probabilistic programming.
- Contributions to open-source LLM reasoning frameworks.
- Familiarity with scientific discovery pipelines in chemistry, biology, or materials science.
- Experience with multimodal reasoning (e.g., combining text, image, and experimental data).
Responsibilities
- Design and formalize frameworks for scientific reasoning with LLMs, including structured prompting, reasoning chains, and test-time compute.
- Explore and implement methods for in-context learning, self-reflection, and adaptive reasoning in scientific discovery workflows.
- Build scalable model prototypes that can be deployed to solve frontier scientific problems.
- Collaborate with scientists and engineers to encode domain knowledge into reasoning systems that integrate symbolic and statistical approaches.
Other
- PhD (preferred) or equivalent research/industry experience in Computer Science, Machine Learning, AI, Engineering, Materials Science or related fields.
- Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
- Publications in top ML/AI conferences (NeurIPS, ICML, ICLR, ACL).
