Lila Sciences is seeking to accelerate discovery and innovation in scientific research through the application of artificial intelligence.
Requirements
- Strong understanding of large language models (LLMs) and their application to scientific problem-solving, with a focus on domain adaptation and task-specific fine-tuning.
- Proficiency in modern ML frameworks (e.g., PyTorch, TensorFlow, JAX) and experience implementing scalable solutions for complex tasks.
- Demonstrated expertise in developing AI agents for complex, long-range tasks.
- Experience building custom benchmarks or evaluation frameworks to test agent performance on domain-specific challenges.
- Familiarity with scientific data pipelines and workflows.
Responsibilities
- Develop AI agents capable of solving complex, domain-specific scientific problems through sequential decision-making and multi-step reasoning.
- Train and fine-tune models to adapt to specific scientific domains, ensuring robust performance on real-world research tasks.
- Implement rigorous testing frameworks and benchmarks to evaluate agent capabilities and measure progress toward scientific objectives.
- Collaborate with cross-functional teams to integrate AI agents into experimental workflows, enabling faster iteration and discovery in areas such as biology, chemistry, and materials science.
Other
- PhD or Masters in a quantitative discipline (e.g., Computer Science, Physics, Mathematics, Engineering) with a strong background in machine learning and one domain of science (e.g. biology or materials science).
- Experience comes in many forms, skills are transferable, and passion goes a long way.
- Inclusive mindset and a diversity of thought.
- Ability to work in unstructured and creative environments.
