Causal
Member of Technical Staff — Research, Atmospheric Science
San Francisco · Staff+
Sponsorship not specifiedDetected 1 day ago
Machine LearningForecastingRoboticsResearchProblem Solving
About the role
- Our founding team has built and deployed AI against the physical world in robotics, drug discovery, and particle physics at institutions like DeepMind, Waymo, Cruise, Insitro, Nabla Bio, and CERN.
- We look for domain experts who are excited to tackle unsolved problems.
Responsibilities
- Partner with model, evaluation, and product teams to translate atmospheric expertise into research direction and credible results
- Ability to collaborate closely with ML researchers and translate domain knowledge into technical requirements
Requirements
- We value a relentless approach to problem-solving, rapid execution, and the ability to quickly learn in unfamiliar domains.
- Deep expertise in atmospheric science, meteorology, or a closely related field (typically a PhD or equivalent research experience)
- Familiarity with operational forecasting, numerical weather prediction, and forecast verification methods
- Comfort working with large observational and reanalysis datasets
- We believe that scaling on physics will enable an understanding of causality required to predict and control physical systems, starting with weather.
- Weather is our first proving ground - the most well-observed physical system on Earth - and getting it right demands deep atmospheric expertise embedded directly in the research.
Company info
- What we're looking for
This listing is sourced directly from Causal's careers page and normalized into a canonical job model.