Take ownership of office operations in a dynamic AI research lab, ensuring compliance and efficient management while supporting a vibrant workspace culture.
About us
Symbolica was founded on a simple idea: intelligence is about structure and reasoning, not just pattern matching.
For decades, AI has been split between symbolic systems that are reliable but brittle and neural systems that are flexible but unpredictable. We’re building a bridge between the two.
We’re an AI research lab combining deep mathematics and machine learning to create systems that truly reason. Using category and type theory as a unifying framework, we develop interpretable, reliable and scalable foundations for intelligence and turn them into real products, working in a tight feedback loop where research directly shapes application.
Agentica is the latest expression of this vision: an agent framework for tool use and multi-agent orchestration through arbitrary code execution. It recently achieved 85.28% on ARC-AGI-2, setting a new public SOTA.
Founded in 2022, we’ve raised over $30M from investors including Khosla Ventures, General Catalyst, Abstract Ventures and Buckley Ventures, backing us to rethink the mathematical foundations of machine learning.
If you’ve ever been kept awake wondering what comes after deep learning, you’ll fit right in.
About the role
As a Part-Time Office Manager, you will take ownership of our office operations, ensuring the space runs smoothly, efficiently, and remains compliant with health and safety regulations. You’ll be responsible for managing vendors, overseeing cleaning and maintenance, stocking supplies, and acting as the primary liaison with building management.
📍 This is an onsite role based in our London office (66 City Rd), requiring 10 hours per week. We offer flexible part-time hours – whether a few full days per week or daily half-days, based on business needs and agreement with the manager – along with competitive compensation aligned with experience.
Your focus
About you
Symbolica AI is an innovative research lab focused on applying category and type theory to enhance logical reasoning in machines. Our cutting-edge technology is designed to empower industries by transforming how AI systems function and interact with complex data.
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