> 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 here, you will be responsible for {mid,post}-training LLMs and helping us build an AI system with quantitative reasoning capability that can perform previously impossible tasks or achieve unprecedented levels of performance in the domain of designing physical systems.

> tech stack

• Python

• PyTorch

• C++

> we expect you to

• have strong programming skills and deep understanding of machine learning

• experience working with large distributed systems

• be comfortable diving into a large ML codebase to debug

• have a deep understanding of LLM architectures

• have experience with LLM {mid,post}-training

• execute and analyze experiments autonomously and collaboratively

• be excited about the prospect of building an engineering AGI

> ++

• you’ve built a popular/impactful open source project

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

• keep up with state-of-the-art LLM research

> you will thrive in this role if

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

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

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

> 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