causal

Member of Technical Staff — Deployment Product

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Older posting · still listed ·

  • onsite
  • FullTime
  • Deployment
  • San Francisco
  • Singapore
Work arrangement
onsite
Employment
FullTime
Stated compensation
Not specified
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Requirements

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Remote policy
onsite
“Provider workplace type: onsite”
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Employment type
FullTime
9 fields not stated in this posting
Employer sponsorship
Not specified
Geographic scope
Not specified
Degree requirement
Not specified
Security clearance
Not mentioned
Timezone / hours
Not specified
Citizenship requirement
Not mentioned
Minimum experience (years)
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Compensation
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READ IT IN THE EMPLOYER’S OWN WORDS

Original job description

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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.
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 About the deployment team 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.  About the role We look for leaders who are excited to tackle unsolved problems and to own the outcome end to end. This is not a traditional product role and you will NOT be managing a backlog from a desk. You will embed with our most strategic customers and lead the cross-functional team — on our side and theirs — that turns our technology into results they can rely on. Willingness to travel to and spend extended time on-site with customers is required. Responsibilities Own the delivery of results for strategic customers, from first engagement through production impact Lead cross-functional deployment teams across both Causal Labs and the customer Embed with customers in their operational environment to understand what winning looks like, and drive relentlessly toward it Coordinate the many moving parts of a complex deployment, keeping every stakeholder aligned and moving Turn what you learn in the field into direction that sharpens the product and the next deployment 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 delivering complex, high-stakes projects for demanding customers or stakeholders Exceptional cross-functional leadership — you get engineers, operators, and executives rowing in the same direction Comfort embedding with customers, including significant travel and time on-site in operational environments Strong technical fluency — enough to lead a technical team and earn its respect, without needing to write the code yourself Ownership, urgency, and the judgment to make the right calls with incomplete information
Original formatting and links

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.

 

About the deployment team

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.

 

About the role

We look for leaders who are excited to tackle unsolved problems and to own the outcome end to end. This is not a traditional product role and you will NOT be managing a backlog from a desk. You will embed with our most strategic customers and lead the cross-functional team — on our side and theirs — that turns our technology into results they can rely on.

Willingness to travel to and spend extended time on-site with customers is required.

Responsibilities

  • Own the delivery of results for strategic customers, from first engagement through production impact

  • Lead cross-functional deployment teams across both Causal Labs and the customer

  • Embed with customers in their operational environment to understand what winning looks like, and drive relentlessly toward it

  • Coordinate the many moving parts of a complex deployment, keeping every stakeholder aligned and moving

  • Turn what you learn in the field into direction that sharpens the product and the next deployment

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 delivering complex, high-stakes projects for demanding customers or stakeholders

  • Exceptional cross-functional leadership — you get engineers, operators, and executives rowing in the same direction

  • Comfort embedding with customers, including significant travel and time on-site in operational environments

  • Strong technical fluency — enough to lead a technical team and earn its respect, without needing to write the code yourself

  • Ownership, urgency, and the judgment to make the right calls with incomplete information

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