LLM Scientist, AI for Science

Job summary

Responsibilities

We are hiring an LLM Scientist to push the boundaries of AI-driven scientific discovery. You will specialize in developing and optimizing large language models (LLMs), agentic AI, and deep learning frameworks to solve open problems in the natural sciences: Biology, Chemistry, Physics, and/or…

• Model-centric innovation: Improving LLMs’ capabilities to tackle complex scientific problems (e.g., literature synthesis, autonomous experimentation, rigorous derivations).
• Cross-disciplinary collaboration: Partnering with Natural sciences domain experts to translate AI advancements into real-world scientific impact.
• AI/ML Research: Participate in end-to-end training of LLM-based solutions, with a focus on scalability, generalization, and scientific applicability.
• Data creation: Design original workflows to accumulate high quality scientific data at scale, either through synthetic or crowd sourced pipelines.
• Algorithm Design: Use and improve reinforcement learning, or agentic systems tailored to Natural sciences challenges (e.g., modeling resolution, material property prediction…

What they're looking for

• AI/ML Expertise: Strong background in LLMs, deep learning, or agentic AI, with a track record of applying these to real-world problems (publications, open-source contributions…
• State-of-the-art Knowledge: Familiarity with the latest advancements in LLM architectures and post training.
• Technical Depth: Hands-on experience with PyTorch/TensorFlow/JAX, model optimization, and scaling techniques (e.g., fine-tuning, RLHF).
• Scientific Capability: Ability to understand 1 Natural Science domain at a high level (e.g., graduate level specialization + general undergrad knowledge) to design effective AI…
• Engineering Rigor: Proficiency in scientific computing (e.g., numerical methods, HPC) and software best practices.

Tech stack

• PyTorch
• TensorFlow
• JAX