We use a management approach that is close to Agile. Among others, we use guided continuous improvement, task prioritisation, sprints, value delivery, and focus on commitment.

Agile Experience.

Abstract thinking.

like Notion, Slack, Zotero, Shortcut, Miro, Git.

Infrastructure Tools

A strong advantage would be

The company develops a system capable of semantic processing of programming code, e.g., code analysis, transformation, and synthesis, as well as operating a computational environment. The approach combines explicit knowledge representation in discrete structures with ML-assisted algorithms to manipulate those structures. The system we design should be able to follow the reasoning trajectory and examine the internal logic; identify a lack of information and interact with external sources; incorporate new knowledge at later stages equally inexpensive as at the initial ones.


Machine Learning / Data Science / Software Engineering

People tend to think that AI is solely Machine Learning, like ChatGPT (or DALL-E 2, or Microsoft Bing, or ChatSonic). We are building our solution on an alternative architecture which incorporates ML as a part.

Not just an ML

We put much effort into profound research and development of new underlying technologies rather than reusing existing ones. We like to explore unfairly neglected and non-conventional approaches to AI.

Going beyond

We want to be responsible in our research and development. We don't turn our noses up at AI safety research and take the issue of alignment seriously.

Safety and Alignment

That is, of course, a very basic condition. We want our colleagues to be healthy, happy and recreated.

Good Salary

Our team members work from both the office and homes all around the world. We are OK with that. However, we like to gather sometimes at the office to get on the same page.

Hybrid Remote

Outside scheduled team meetings, teammates are free to work on their tasks independently. When to work is a personal choice. Just do not overwork – that is inefficient.

Flexible Schedule

High autonomy is crucial for us – the small and agile team can achieve a breakthrough if its members are professional and independent. However, we promote helping each other. That is crucial too.

Autonomy

Automated code synthesis is a holy grail: many want it, but nobody has it. You can read more about it on the Company tab or just write to us. We love cross-pollination.

Challenging Work

What we value most are performance and results, not a strict process following. However, metrics, processes, and documentation are important too. We just keep their priorities low.

Low Bureaucracy

What we are offering

Running open-sourced models on our hardware.

Building pipeline for distributed training.

Integrating models with the rest of our systems.

Staying on top of architectures and frameworks.

Analysing and suggesting improvements for datasets.

In-depth knowledge of: Machine Learning, Deep Learning, Training customisation, ML frameworks.

Known architectures: Transformer, LLM, GNN, Autoencoders.

Bachelor’s degree or higher. English C1 or higher.

Who we are looking for

Make and fulfil commitments on time and at a high-quality level.

Commitment.

Ability to figure out how to do new tasks from adjacent specialisations.

All-Round.

Focus on the objective, looking for new approaches, fast forwarding orientation.

Startup Mindset.

Presenting own arguments, listening to others' arguments, developing the next steps to resolve the difficulty.

Constructive Discussion.

What soft skills are essential

You respect key deadlines and pass on the results of your work to your teammates in an appropriate condition.

Individual responsibility.

You recognise areas for growth and proactively learn new skills and knowledge for your current and prospective areas of responsibility.

Lifelong learning.

You can plan your work several weeks ahead and can juggle multiple projects at once. You know when to postpone a task to keep your workload manageable.

Vision & planning.

You cover every important aspect of your task leaving out no crucial detail.

Thoroughness.

You offer help if you have spare capacity. You take initiative and pitch your own projects to others.

Proactiveness and initiative.

You question every judgement, claim or number and can engage in a healthy debate with your teammates.

Critical thinking.

You can challenge existing ways, abandon well-trodden paths and embrace the new in the name of the great.

Dynamic, out-of-the-box mindset.

Personal qualities

Noeon Research is an ambitious deep-tech startup working on a novel natively agentic graph-neuro-symbolic system with general capabilities. We are an international 30-people team with headquarters in Tokyo, Japan.

We are developing Noeon – a novel natively agentic AI system with general capabilities based on carefully selected principles from mathematical category theory, knowledge representation, and computational linguistics. Our technology prioritises interpretability, revisability, and generality, allowing for safe and efficient adaptation to a changing world. We prioritise AI safety by focusing on interpretability in order to unlock capabilities safely.

 Software Engineering, Computer Science, Mathematics

Depending on the candidate's skill level, our target salary range is 14-20M JPY per year for a full-time position and equity compensation (options).

Competitive Salary

Compensation of overseas health insurance and additional medical costs, yearly health checkup.

Medical Allowance

Support for English and Japanese language training.

Language Courses

Visa Sponsorship, Relocation Allowance, Travel Allowance, Monthly commute expense in Japan, Japanese Social Security.

Other

Design algorithms and data structures for the Noeon’s architecture.

Measure and optimise performance of system critical components.

Collaborate with cross-functional teams to define product requirements and deliver solutions aligned with organizational goals.

Responsibilities and Expectations

At least 5 years of experience in Software Engineering, Data Structure and Algorithm Engineering.

[essential]

Hands-on experience in design/optimisation of parallel algorithms.

[advantageous]

Experience

Experience in Graph Algorithms, Performance optimization, performance evaluation.

[essential] 

Ability to design/optimize complex algorithms and data structures.

[required]

Knowledge of Algorithms and Data Structures.

Familiarity with the low-level optimization.

Technical skills

Degrees in Software Engineering, Computer Science, Mathematics, or a related technical discipline.

Educational background

Proactive mindset to stay updated with the latest advancements in AI.

Fluent in conversational and written business English (C1+).

Ability to work collaboratively in cross-functional teams.

Experience working using Agile framework.