Member of Technical Staff — Research, Operations & Decision Science

Causal LabsSan Francisco, California

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Overview

Schedule

Full-time

Career level

Senior-level

Remote

On-site

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. A prediction matters most when it leads to better decisions — and evaluating decision quality in high-stakes operational environments is a challenge on its own. Your mission is to bring that discipline to our reasoning research: defining the objectives our models optimize toward and the methods by which we judge whether their decisions are actually good.

Responsibilities

Formulate the objectives, constraints, and decision problems that our reasoning models optimize toward
Develop methodology for evaluating decision quality under uncertainty, including counterfactual reasoning about outcomes
Translate the realities of complex operational environments into well-posed optimization and decision problems
Bring rigor to how optimization and decision-making models are validated for real-world use
Partner with reasoning, evaluation, and product teams to connect research to the decisions it ultimately informs

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 operations research, decision science, or a closely related field (typically a PhD or equivalent experience)
Strong grasp of optimization and decision-making under uncertainty, ideally including stochastic methods
Experience in high-stakes operational settings where forecasts drive consequential decisions
Particular strength in evaluating the quality of optimization or decision models, not just building them
Ability to collaborate closely with ML researchers and translate operational realities into technical problems

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FAQs About Member of Technical Staff — Research, Operations & Decision 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.

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