> about P-1 AI

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—helping mankind conquer nature and bend it to our will. Our first product is Archie, an AI engineer capable of quantitative and spatial reasoning over physical product domains that performs at the level of an entry-level design engineer. 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 just closed a $23 million seed round led by Radical Ventures that includes a number of other AI and industrial luminaries (from OpenAI, DeepMind, etc.).

> about the role

As a Research Engineer (VLM post-training) here, you will be responsible for post-training and deploying VLMs (vision language models) and endowing them with quantitative reasoning capability so that they can perform previously impossible tasks or achieve unprecedented levels of performance in the domain of designing physical systems. You will also help our systems become capable of utilizing complex GUI-based software tools. We're looking for people with solid engineering skills, writing bug-free machine learning code, and building the science behind the systems employed (algorithms, data, evals). You will get exposure and will be expected to solveand take ownership of components across the entire stack. You will be interfacing with simulation engineering and domain experts to deploy this technology on real-world problems.

> tech stack

• Python

• PyTorch

• C++

> location

This is a hybrid role but principally based in San Francisco. Candidates are expected to be located in the Bay Area or open to relocation.

> we expect you to

• have strong programming skills and deep understanding of machine learning

• have experience working with large distributed systems

• be comfortable diving into a large ML codebase to debug

• have a deep understanding of VLM architectures

• have experience with VLM post-training and inference

• execute and analyze experiments autonomously and collaboratively

• be excited about the prospect of building an engineering AGI

> ++

• keeping up with state-of-the-art VLM research

• you’ve built an impactful/popular open-source project

• you’ve published/co-authored papers on VLMs

> you will thrive in this role if

• you have a background in statistical machine learning, physics, mathematics, or another theoretically and empirically rigorous field

• you love working in a fast-paced, dynamic startup environment

• you are intellectually curious and quick to pick up concepts outside of your direct areas of expertise

> interview process

• Initial screening - with Head of Talent (30 mins)

• Hiring manager interview - with co-founder & Head of AI (30 mins)

• Technical interview 1 (60 mins)

• Technical interview 2 (60 mins)

• Culture fit / Q&A (maybe in-person) - with co-founder & CEO