Causal
Member of Technical Staff — Research Engineering, Evaluation
San Francisco · Staff+
Sponsorship not specifiedDetected 1 day ago
Full-Stack DevelopmentStatisticsRoboticsResearchProblem 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 research engineers who are excited to tackle unsolved problems.
- Progress is only as trustworthy as its measurement.
Responsibilities
- Design and build a central, reusable evaluation framework that every model and every team runs through
- Implement evaluation pipelines, benchmark suites, and baselines that make model quality measurable and comparable across efforts
- Build the visualization and dashboard tools that turn raw results into shared, actionable understanding for the whole team
- Partner with research and domain teams to translate what "good" means in each domain into standardized, automated metrics
- Strong software engineering skills and experience building data or evaluation pipelines at scale
- Solid grasp of probability and statistics, with the judgment to design evaluations that measure what they claim to
- Full-stack range: comfortable building both backend pipelines and the frontend tools people read results in
- Owns deliverables end-to-end, from collecting requirements to autonomously driving execution
Requirements
- We value a relentless approach to problem-solving, rapid execution, and the ability to quickly learn in unfamiliar domains.
- Experience turning research or model outputs into metrics, benchmarks, and visualizations that teams rely on
- We believe that scaling on physics will enable an understanding of causality required to predict and control physical systems, starting with weather.
Company info
- What we're looking for
This listing is sourced directly from Causal's careers page and normalized into a canonical job model.