Causal
Member of Technical Staff — ML Research, Multimodal
San Francisco · Staff+
Sponsorship not specifiedDetected 2 days ago
AlgorithmsMachine LearningComputer VisionForecastingRoboticsSensorsResearchProblem 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 researchers who are excited to tackle unsolved problems.
Requirements
- We value a relentless approach to problem-solving, rapid execution, and the ability to quickly learn in unfamiliar domains.
- Experience training large-scale models and the ability to understand experimental results through careful analysis and ablation studies
- Familiarity with distributed training and the systems considerations of scaling models
- A track record of turning open-ended research problems into production models
Skills
- Work across the full ML stack - data, model, eval, and infrastructure - to take ideas from prototype to scaled training runs
- Stay up-to-date on research to bring new ideas to work
Benefits
- Strong grasp of machine learning fundamentals, with depth in at least one relevant domain (e.g. sequence or world models, computer vision, sensor fusion, generative modeling, physics-informed NNs)
Company info
- What we're looking for
- Our mission is general causal intelligence; AI that is capable of (1) predicting the future and (2) identifying the actions to alter it.
This listing is sourced directly from Causal's careers page and normalized into a canonical job model.