Tuyển dụng Senior Research Engineer — Cognitive Systems tại Hồ Chí Minh

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.

Experience we would especia

Yêu cầu công việc

Experience we would especially value

• Computational cognitive science or computational models of psychological processes.

• Longitudinal evaluation of interactive or learning systems.

• Speech interaction, computer vision or human–computer interaction.

• Private model deployment, adaptation or inference on constrained hardware.

• Research collaborations that produced working systems or substantive experimental findings.

• An established academic network is welcome. Your ability to identify the right expertise and collaborate effectively matters more than existing university affiliations.

• A particular degree is not a prerequisite. Show us the quality of your work through research, deployed systems, open-source contributions or rigorous independent projects.

Your first contributions

• You will begin by examining the existing research, code and product concepts. Identify what is implemented, what is hypothesised and where the most consequential uncertainties lie.

• Together, we will select a bounded research question. You will build a reproducible experiment, compare it against a credible baseline and recommend the next step.

• From there, you will investigate how faculties interact across repeated experiences, making their individual contributions and failure modes inspectable.

How we judge progress

• Progress means building useful mechanisms and reducing uncertainty.

• A well-supported negative result can be more valuable than an impressive demonstration. We expect our architecture to change when the evidence demands it.

• We distinguish observable behaviour, computational mechanisms and claims about subjective experience. Fluent language or simulated emotion alone establishes neither lasting development nor consciousness.

Why this role

• You will help shape a foundational architecture while its central questions are still open.

• The work connects research with something people can encounter: an embodied system that sees, listens, participates in shared work and carries a history forward.

• Your contribution will influence what MYCL becomes, how we evaluate it and which ambitions survive contact with evidence.

• Show us how you think

• Share a project, paper, repository or experiment that demonstrates your ability to build and investigate.

Tell us:

• What was the central uncertainty?

• What did you implement?

• How did you test it?

• What result changed your mind?

• We are particularly interested in work where your conclusions became stronger because you challenged your original idea.

Quyền lợi

• Thưởng: Theo quy định công ty