Founding Research Engineer/Scientist

About usWe are an early-stage AI company building adaptive systems that understand users, their goals, preferences, and changing context over time.Our work sits at the intersection of frontier AI, user modelling, cognitive science, and human-computer interaction. The company was founded by a former Google DeepMind Research Scientist (Gemini), and we work closely with researchers at the Consciousness and Cognition Lab at the University of Cambridge on computational models of cognition, subjective experience, and human state.Our emerging founding team brings together experience from DeepMind, Meta AI, Oxford, and high-scale technology companies, spanning machine learning, personalized systems, and cognitive neuroscience.RoleWe are looking for a full-time, London-based Founding Research Engineer to help build the company’s core technology from the ground up.You will work directly with the founder across research, engineering, and product, developing systems for:user modelling and personalization;memory and long-term context;adaptive model behaviour;evaluation and experimentation;frontier and open-weight model integration.This is a hands-on founding role. You will translate research ideas into working systems, help define the technical architecture and roadmap, and contribute to the engineering culture and future team.The role is best suited to someone who combines strong ML engineering with scientific curiosity and wants meaningful ownership at the earliest stage of a company.Who you are6+ years of professional experience building and deploying production machine learning systems.Strong software engineering skills and experience building ML systems end to end.Practical experience with LLMs, foundation models, or generative AI.Experience building production ML systems, APIs, data pipelines, or distributed software.Ability to operate independently, move quickly, and make good decisions under ambiguity.Strong communication skills and a collaborative, low-ego working style.A desire to take ownership beyond a narrowly defined engineering role.Ideally, you have experience...Post-training, reinforcement learning, evaluation, or alignment.Personalization, recommender systems, user modelling, or memory.AI agents, adaptive systems, or human–AI interaction.Scalable model infrastructure, distributed training, or inference systems.Experience at a frontier AI lab or leading AI startupStrong open-source contributions, publications, or other evidence of exceptional technical work.PhD in machine learning, computer science, or equivalent industrial experience.Strong publication track record (ACL, NeurIPS, ICLR, ICML, etc).