Description
We are seeking a Senior Principal Scientist to invent and build the next generation of evolutionary algorithms for our autonomous system capable of exploring large scientific and computational search spaces.
In this role, you will develop methods that enable populations of models, hypotheses, programs, or scientific representations to evolve over time through iterative search, selection, variation, and evaluation.
Key responsibilities include:
- Designing and implementing algorithms for autonomously generating and evolving populations of candidate solutions at scale.
- Developing principled methods for maintaining population diversity.
- Building Bayesian and probabilistic frameworks for evaluating and ranking candidates.
- Defining and validating quantitative metrics of diversity and quality.
- Partnering with research and engineering teams to integrate these algorithms into closed-loop autonomous science pipelines.
- Establishing benchmarks and ablations to demonstrate the effectiveness of evolved populations.
Qualifications:
- PhD in a quantitative field with a strong research track record, or equivalent demonstrated expertise with 5+ years of experience post PhD.
- Deep expertise in advanced Bayesian causal modeling and/or evolutionary programming.
- Demonstrated ability to design novel algorithms and bring them to working implementations.
- Strong software engineering skills and experience with computational experiments at scale.
- A record of scientific leadership recognized by the field.
The salary range for this role is $208,000 - $286,000. We offer various benefits, including healthcare coverage, annual incentive program, and retirement benefits.