Deployment Strategist
Causal Labs
Deployment Strategist
Causal Labs
Trains physics AI models to forecast weather
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.
A model only matters if it changes what happens in the real world. Our deployment teams embed directly with the institutions that make the highest-stakes decisions about physical systems. They turn our models into results those institutions can depend on and carry everything we learn in the field back into the product. Deployment works in small, cross-functional pods and partners closely with Product Engineering, which builds the platform the pods deploy.
We look for people who lead through influence and turn the hardest problems into real outcomes. As a Deployment Strategist, you own the holistic set of actions it takes to help a customer win with our technology — starting from their mission, not our software. Your job is to find the true problem, break it into workflows, align everyone from the C-suite to the front-line operator, and drive the solution all the way to impact.
Willingness to travel to and spend extended time on-site with customers is required.
Responsibilities
Identify the true problem limiting a customer's mission, understanding their requirements deeply enough to identify when the problem is not the one they first describe
Decompose that problem into its component workflows, and design solutions backwards from how people actually work
Align stakeholders across the customer's organization, from executives to front-line operators
Own the full set of actions — technical, operational, and organizational — required to reach real impact
Partner with Forward Deployed Engineers and Product Managers to build and deliver the software and AI solutions that win
What we're looking for
We value a relentless approach to problem-solving, rapid execution, and the ability to quickly learn in unfamiliar domains.
A track record of driving complex initiatives to outcomes by leading across organizations
Strong problem decomposition and structured thinking — you find the real problem and solve backwards from the user
Exceptional stakeholder management and the leadership to align people at every level
Enough technical fluency to partner credibly with engineers and shape a real solution
Willingness to embed with customers, including travel and time on-site
A facilitator's instinct: you pair deep rigor with the leadership that moves people
Trains physics AI models to forecast weather
Causal Labs is an AI research company building a foundation model of physical systems for industries whose operations turn on the weather. The company trains on atmospheric sensor and observation data rather than text or images, a domain where cause and effect are governed by physics and yesterday's prediction can be scored against what happened. It runs early pilots with commercial partners and pairs researchers with engineers who deploy the models on customer data. Unlike conventional forecasters, which report what conditions are likely, it is also trying to identify which interventions would change an outcome. The company's goal is to make AI reason about cause and effect by grounding it in the most heavily observed physical system available.
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