Causal AI Researcher — PyTorch & Physics-Based Modeling

Fluency Digital, Inc.; San Francisco (CA); On-site; USD 100,000 - 130,000; Full time

Job summary

Fluency Digital, Inc. is seeking a researcher to architect PyTorch models that infer causal structures from raw data in San Francisco. This role emphasizes understanding physical laws over simple statistical correlations.

The ideal candidate will have at least 1 year of experience in building models using PyTorch, strong Python skills, and an interest in causal inference. A collaborative approach and deep focus are valued in this innovative environment.

Qualifications

• 1+ years of hands-on experience in building and training models with PyTorch.
• Strong foundation in Python and scientific computing libraries.
• Deep interest in causal inference, physics-based modeling, or representation learning.

Responsibilities

• Architect novel PyTorch models inferring causal structures from raw data.
• Translate complex research concepts into robust engineering implementations.
• Contribute to understanding physical laws rather than just statistical patterns.

Skills

PyTorch model building and training

Python programming

Causal inference

Scientific computing

Job description

Fluency Digital, Inc. is seeking a researcher to architect PyTorch models that infer causal structures from raw data in San Francisco. This role emphasizes understanding physical laws over simple statistical correlations.

The ideal candidate will have at least 1 year of experience in building models using PyTorch, strong Python skills, and an interest in causal inference. A collaborative approach and deep focus are valued in this innovative environment.