Lila Sciences is seeking an AI Lab Research Engineer to develop AI models that can tackle complex, multi-step problems across domains.
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.
- Contributions to high-impact research in machine learning and AI, particularly in areas such as sequential decision-making, reasoning, or multi-step problem-solving (e.g., publications in top-tier conferences like NeurIPS, ICML, AAAI, ICLR).
- 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).
- Commitment 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.
