About you:
have done something remarkable, and have undeniable real-world proof-of-talent you can share with us
go from 0 → 1 on an idea before breakfast
always learning
believe in manifesting the future of physical engineering
About us:
We are building an engineering AGI. We founded P-1 AI with the conviction that the greatest impact of artificial intelligence will be on the built world. Our first product is Archie, an AI engineer capable of quantitative intuition over physical product domains and engineering tool use. Archie initially performs at the level of an entry-level design engineer but rapidly gets smarter and more capable. We aim to put an Archie on every engineering team at every industrial company on earth.
Our founding team includes the top minds in deep learning, model-based engineering, and industries that are our customers. We closed a $23 million seed round led by Radical Ventures that includes a number of other AI and industrial luminaries (from OpenAI, DeepMind, etc.).
In summary:
we are on a mission
multiple hats is the norm
no politics, low bureaucracy
fast, data-driven decision-making; velocity and agility are everything
believe in manifesting the future of physical engineering
About the role:
We are a small team tackling an ambitious problem. If we are successful, it will change the course of history. As such, we have a very high talent bar and are looking for people who have done something remarkable.
This role builds the physics simulators that teach Archie how the real world works. You will develop first-principles, acausal models of thermofluid and electrical systems and use them to generate large-scale synthetic datasets that power Archie’s reasoning about physical systems.
You will work on chillers, air handlers, cooling towers, hydronic networks, switchboards, transformers, and distribution systems—sweeping your models across thousands of operating conditions, fault modes, and design variants. The fidelity of your simulations directly determines the capabilities of our AI.
You will collaborate closely with ML engineers to ensure simulation outputs translate into real-world performance.
We don’t care if you’ve done it before. We just need you to be brilliant, mission-driven, and thirsty to learn.
This role can be either remote (based in the US or Canada and with existing work authorization) or based in our SF office. If you are remote, you should plan to spend one week out of six co-working with the rest of the company in our SF office. We will support relocation for candidates interested in moving to SF.
Compensation:
$150 - $200k… for now. This role includes a significant equity component. We are an early-stage startup, so we favor equity over cash in our current compensation philosophy. You should too, or an early-stage startup might not be for you. That said, we expect cash compensation to progress quickly as the company matures.
Our benefits include healthcare, dental, and vision insurance, 401k with employer matching, and unlimited PTO.
Interview process:
Initial screening call (30 mins)
Biographical/behavioural interview (45 mins)
Technical interview (60 mins)
CEO interview (30 mins)
