We're building a digital being.
An individual with a history of its own. One that learns through experience, develops interests, forms judgements and builds a lasting relationship with a human. A being whose identity persists as its models, capabilities and physical body evolve.
Making this real requires answers to difficult questions. How does an experience become a memory that changes future behaviour? How do attention, affect and motivation shape judgement? What should remain stable as an individual develops-and what should be free to change?
As a Founding Research Engineer, you will help define and build these mechanisms. You will work at the intersection of AI, cognitive science and human interaction, turning ambitious ideas into systems we can test, challenge and improve.
You will have the scope to shape MYCL's foundations, pursue original hypotheses and overturn assumptions-including ours.
The challenge is to make individuality, development and responsibility properties of the system itself.
What you will do
• Build mechanisms. Translate concepts into computational hypotheses and working prototypes. Connect models with persistent state, memory and processes that operate across repeated experiences.
• Design decisive experiments. Establish baselines, controlled comparisons and ablation studies. Define in advance what evidence would support, weaken or falsify a hypothesis.
• Study development over time. Evaluate continuity, learning, judgement and reliable commitments across interactions. Investigate failures that a polished demonstration can conceal.
• Shape the architecture. Work with the technical lead on component boundaries, state ownership and the allocation of computation across the body and optional private infrastructure.
• Connect internal processes with experience. Work with interaction design on voice, camera and shared workspaces, making attention, uncertainty and proposed actions understandable to a human.
• Bring science into engineering. Critically assess relevant work in AI, psychology and cognitive science. Initiate focused collaborations where external expertise can resolve a concrete research question.
• Make clear recommendations. Document results and limitations. Explain when we should continue, change direction or remove a mechanism.
What you will own
• You will own the experimental quality of our faculty research: hypotheses, implementations, evaluation methods, reproducibility and interpretation.
• You will help shape the cognitive architecture with the technical lead and contribute directly to product decisions through evidence.
• This is a hands-on founding role. Writing code, inspecting behaviour and debugging experiments are central to the work.
What you bring
• Strong
software engineering skills, particularly in Python, and experience building reproducible ML experiments.
• Practical experience with modern language or multimodal models, inference and evaluation.
• Depth in at least one relevant area: memory and learning, reasoning and planning, cognitive architectures, multimodal perception, affective computing or computational motivation.
• Experience building systems whose behaviour depends on state and history across interactions.
• Strong experimental judgement: meaningful baselines, controlled comparisons, failure analysis and careful interpretation.
• Enough grounding in cognitive science or relevant psychology to engage critically with theories of attention, memory, emotion, motivation and learning.
• The ability to turn an unfamiliar research question into a tractable investigation.
• Intellectual independence and clear communication across engineering, research and design.
• You do not need to be an expert in every faculty. We are looking for depth, strong judgement and the ability to connect disciplines.