Principal Category Theory Scientist - AUS - Categorical Deep Learning

at  Symbolica AI

DESCRIPTION

At Symbolica, we are building deep learning models which perform structured reasoning: manipulate structured data, learn algebraic structure in it, and do so with an interpretable and verifiable logic. To that end, we are developing new mathematical foundations for deep learning: categorical deep learning. We are now assembling a R&D lab of expert category theory and machine learning researchers to develop this theory and apply it to the problems of code synthesis and theorem proving. We are committed to fundamental ideas, but also their execution in practice.
As a principal category theory scientist, you will help us expand, refine, and carry out our research & development program. You will help design internal company procedures, assist with financial planning, and staff teams developing and implementing the theory of categorical deep learning. This is a rare opportunity to work on an innovative and transformative project, and make significant contributions to the field of applied category theory and artificial intelligence. This is a high-impact role in which you will help shape the company; we are looking for advanced researchers and skilled leaders.

Responsibilities:

• Lead the development and ownership of pioneering research projects in categorical deep learning, from conceptualisation to execution, while ensuring alignment with Symbolica’s strategic objectives
• Assist with staffing, financial planning and public engagement of the company
• Work closely with category theorists and machine learning researchers, bridging the gap between state of the art research on deep learning architectures and their structural formulation in category theory
• Stay at the forefront of category theoretic advances, and ensure our deep learning models are grounded and coherent with respect to them
• Grow, lead and mentor a team of category theorists and machine learning researchers
• Lead a team prototyping and validating theoretical models in code, demonstrating practical feasibility
• Work simultaneously at different levels of abstraction - from understanding high-level categorical constructions to implementing low-level details of architecture in code

Preferred qualifications:

• PhD in Mathematics, Computer Science, Machine Learning or similar discipline
• 5+ Years experience after doctorate
• Industrial or academic experience leading a research/technical team, and implementing novel machine learning architectures
• Expertise in category theory or type theory, and a strong interest in machine learning
• Exceptional communication and interpersonal skills
• Experience establishing the culture of early-stage organisations

Location:

• Melbourne (preferred) or AUS remote

We offer competitive compensation, including equity and health insurance. Salary and equity levels are commensurate with experience and location.

• Lead the development and ownership of pioneering research projects in categorical deep learning, from conceptualisation to execution, while ensuring alignment with Symbolica’s strategic objectives
• Assist with staffing, financial planning and public engagement of the company
• Work closely with category theorists and machine learning researchers, bridging the gap between state of the art research on deep learning architectures and their structural formulation in category theory
• Stay at the forefront of category theoretic advances, and ensure our deep learning models are grounded and coherent with respect to them
• Grow, lead and mentor a team of category theorists and machine learning researchers
• Lead a team prototyping and validating theoretical models in code, demonstrating practical feasibility
• Work simultaneously at different levels of abstraction - from understanding high-level categorical constructions to implementing low-level details of architecture in cod