Member of Technical Staff — Research, Atmospheric Science

Causal LabsSan Francisco, California

Apply with Sonara

Automate your job search with Sonara.

Submit 10x as many applications with less effort than one manual application.¹

Reclaim your time by letting our AI handle the grunt work of job searching.

We continuously scan millions of openings to find your top matches.

Overview

Schedule

Full-time

Career level

Senior-level

Remote

On-site

Benefits

Career Development

Job Description

Our mission is general causal intelligence; AI that is capable of (1) predicting the future and (2) identifying the actions to alter it.

To achieve this breakthrough, we are building a Large Physics foundation Model (LPM) because physical systems, unlike text or images, are governed by verifiable cause and effect. We believe that scaling on physics will enable an understanding of causality required to predict and control physical systems, starting with weather.

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. 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. Your mission is to bring that expertise to bear on every part of the model: what data we learn from, how we know the model is correct, and where it still falls short.

Responsibilities

Guide the sourcing and validation of atmospheric data, advising on observation systems, their characteristics, and their pathologies
Define what forecast quality means, bringing rigorous verification methodology to how we evaluate the model
Run case studies on high-impact events to probe model behavior and surface failure modes
Benchmark against operational numerical weather prediction baselines and the state of the field
Partner with model, evaluation, and product teams to translate atmospheric expertise into research direction and credible results

What we're looking for

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
Ability to collaborate closely with ML researchers and translate domain knowledge into technical requirements
A rigorous, evidence-driven approach to evaluating model quality

Automate your job search with Sonara.

Submit 10x as many applications with less effort than one manual application.

Apply with Sonara Apply manually

FAQs About Member of Technical Staff — Research, Atmospheric Science Jobs at Causal Labs

What is the work location for this position at Causal Labs?

This job at Causal Labs is located in San Francisco, California, according to the details provided by the employer. Some roles may also include multiple work locations depending on the requirement.

What pay range can candidates expect for this role at Causal Labs?

Employer has not shared pay details for this role.

What employment applies to this position at Causal Labs?

Causal Labs lists this role as a Full-time position.

What experience level is required for this role at Causal Labs?

Causal Labs is looking for a candidate with "Senior-level" experience level.

What benefits are offered by Causal Labs for this role?

Causal Labs offers Career Development for this position. Actual benefits may vary depending on the employer's policies and employment terms.

What is the process to apply for this position at Causal Labs?

You can apply for this role at Causal Labs either through Sonara's automated application system, which helps you submit applications 10X faster with minimal effort, or by applying manually using the direct link on the job page.