
Noeon Research is a deep-tech startup focused on creating a new architecture for general reasoning in AI. Their innovative approach combines category theory, graph-based knowledge representation, and computational theory to develop a universal knowledge representation for computations. This architecture aims to enhance interpretability, reliability, security, and continual learning, positioning Noeon as a leader in the AI space with a commitment to trustworthy and interpretable general intelligence.

Noeon Research is a deep-tech startup focused on creating a new architecture for general reasoning in AI. Their innovative approach combines category theory, graph-based knowledge representation, and computational theory to develop a universal knowledge representation for computations. This architecture aims to enhance interpretability, reliability, security, and continual learning, positioning Noeon as a leader in the AI space with a commitment to trustworthy and interpretable general intelligence.
Company Description
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 looking for an aspiring professional to join our RnD team.
Responsibilities and Expectations
• Design, build, and maintain production-grade ML systems with a strong focus on Large Language Models (LLMs).
• Own and evolve the LLMOps lifecycle: data preparation, fine-tuning, evaluation, deployment, monitoring, and iteration.
• Develop evaluation frameworks for LLM quality, robustness, and regression tracking.
• Collaborate closely with researchers, product engineers, mathematicians, and infrastructure teams to translate research prototypes into reliable production systems.
• Contribute to architectural decisions around agentic systems, RAG pipelines, and hybrid ML + symbolic components.
Experience
• 3+ years of experience in Machine Learning or Applied AI roles.
• Hands-on experience deploying ML models to production environments.
• Practical experience with LLMs (open-source or proprietary) in real-world applications.
• Experience operating ML systems under production constraints (latency, cost, observability, reliability).
• Experience working in fast-moving startup or R&D-driven environments is a strong plus.
Technical skills
• Strong Python proficiency; experience with ML frameworks.
• Solid understanding of modern LLM stacks: fine-tuning, inference optimization, RAG, prompt/agent orchestration.
• Experience with MLOps / LLMOps tooling: experiment tracking, evaluation pipelines, monitoring, CI/CD for models.
• Familiarity with containerization and deployment (Docker, Kubernetes or equivalents).
• Experience with cloud or on-prem GPU environments.
• Understanding of distributed systems concepts is a plus.
Educational Background
Bachelor’s or Master’s degree in Computer Science, Machine Learning, Engineering, or a related field (or equivalent practical experience).
Essential Soft Skills
• 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.
Personal Qualities
• Individual responsibility.
You respect key deadlines and pass on the results of your work to your teammates in an appropriate condition.
• Lifelong learning.
You recognise areas for growth and proactively learn new skills and knowledge for your current and prospective areas of responsibility.
• Vision & planning.
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.
• Thoroughness.
You cover every important aspect of your task leaving out no crucial detail.
• Proactiveness and initiative.
You offer help if you have spare capacity. You take initiative and pitch your own projects to others.
• Critical thinking.
You question every judgement, claim or number and can engage in a healthy debate with your teammates.
• Dynamic, out-of-the-box mindset.
You can challenge existing ways, abandon well-trodden paths and embrace the new in the name of the great.
How we are different
• Beyond ML. 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 a different architecture where ML is just a part.
• High-Tech. We put much effort into profound research and development of new underlying technologies rather than reusing existing ones.
• Startup. We have a little regulations and a lot of freedom for our colleagues to propose solutions.
What we are offering
• Our target salary range is 16-22M JPY per year for a full-time position and equity compensation (options).
• Flexible Schedule.
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.
• Autonomy.
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.
• Low Bureaucracy.
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.
• Medical Allowance.
Compensation of additional medical costs, yearly health checkup.
• Language Courses.
Support for Japanese language training.
• Other.
Visa Sponsorship, Relocation Allowance, Travel Allowance, Commute Allowance, Japanese Social Security, Maternity & Childcare leave, Life Support.
Contact us:
hiring@noeon.ai