Thank you for your interest in joining our talent pool of Research Engineers.

Overview

We are not currently actively filling roles on our Research Engineering team, but we are still happy to consider applications from exceptional candidates to design, build, and optimize state of the art models for code synthesis and theorem proving.

Description

Symbolica is building new technology for large-scale AI using structured, interpretable reasoning. The SF Bay Area-based Research Engineering team is focused on overcoming limitations of the autoregressive transformer framework in order to build new foundational models specifically for automated theorem proving and code synthesis.We would be thrilled to receive your application if:

• You are strongly motivated to develop new deep learning models for complex structured reasoning tasks. You like to get your hands dirty to solve hard problems. You love collaborating with other highly intelligent and driven teammates. Personal references can be one way to demonstrate these traits

• You have experience designing and implementing new algorithms for hard problems (including areas outside of machine learning). One way to demonstrate this experience is in a Github repository

• You have a deep understanding of relevant research areas in deep learning, including: diffusion models, large language models, retrieval-augmented generation, knowledge graph generation and traversal, automated theorem proving, code synthesis. One way to demonstrate this understanding is with a record of publications in venues such as ICML, ICLR, and NeurIPS

• You have a strong mathematical foundation. A Ph.D. in math, physics, or theory of computing is one way to demonstrate this background

In-person in our San Carlos office is preferred, but we will be happy to consider exceptional candidates in other locations.