Founding AI Research Engineer

This role is with one of Dex's trusted partner companies. We work closely with their teams to truly understand their culture, goals, and what they're looking for, so we can match you with the right opportunity and give you context about the role before you commit to a process.

Dex is an AI recruiter agent that helps you run your job search. Tell Dex your stack, seniority, and what you want to build. We will manage your applications and surface other opportunities that are a fit.

This company is building a proactive AI assistant that maintains a living model of a person's entire work history — emails, messages, meetings, documents. It acts on their behalf, drafting replies and preparing for meetings, all before being asked. The core challenge is building long‑term memory that stays current, retrieving messy context across diverse sources, and reasoning about information live on screen.

This is a genuinely unsolved problem in AI.

You will own the research direction for these core problems, working end‑to‑end from hypothesis to production. This is applied research, not a publication track: you won't hand off your work to an engineering team, nor will anyone else product ionise it for you. The team is small, composed of repeat founders with doctorates, and they are hiring multiple people into this foundational role.

• Design and implement novel retrieval and knowledge‑base systems for a persistent, living model of user context.
• Develop and deploy reasoning models that operate across diverse, messy data sources.
• Build models capable of real‑time reasoning over live screen and application context.
• Take research from initial hypothesis and experimentation through to robust, production‑ready systems, owning the entire lifecycle.

• A PhD or personally owned a hard, end‑to‑end technical project at a company.
• 5+ years solving research‑level problems in NLP, LLMs, or adjacent ML, in academia or industry.
• You implement and build upon current research papers, not just apply existing libraries.
• You've run both halves of the work: forming and testing hypotheses, and building robust, scalable systems.
• Strong Python, comfortable with cloud infrastructure, and both SQL and No
  
  SQL databases.
• Work in person in Elephant and Castle five days a week.