Lead LLM Engineer
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.
Keywords
Graph-based Representations, Symbolic Logic Frameworks, Machine Learning, Retrieval-Augmented Generation, GPT, LLaMA, T5, BERT, Python, TensorFlow, PyTorch, Hugging Face Transformers, GPU/TPU acceleration, Product Management, Project Management.
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Overview
Country
Japan
City
Tokyo
Category
LLM Engineering
Required Background
Computer Science, Mathematics, Computational Linguistics
Location
Tokyo / APAC preferred for a better time zone overlap with the Tokyo HQ
Outside Tokyo
Available but not preferred
Relocation
Required. Willingness to business travel for 1-2 months 3-4 times a year is also welcome
Employment Type
Full-Time
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Responsibilities and Expectations
Develop and implement solutions leveraging open-source large language models (LLMs) to work with formal languages.
(01)
Fine-tune, customize, and optimize open-source LLMs for various applications, ensuring high accuracy and efficiency.
(02)
Evaluate and compare different open-source LLM architectures to select the most suitable models for given tasks.
(03)
Integrate LLMs into existing systems, ensuring seamless functionality and performance.
(04)
Stay updated with advancements in the field of natural language processing (NLP) and open-source LLMs, incorporating new methods and tools as appropriate.
(05)
Collaborate with cross-functional teams to define product requirements and deliver solutions aligned with organizational goals.
(06)
Experience
[essential]
(01)
Proven experience in working with large language models (e.g., GPT, LLaMA, T5, BERT).
[essential]
(02)
At least 5 years of experience in Machine Learning or Natural Language Processing (NLP).
[essential]
(03)
Hands-on experience in fine-tuning and deploying language models for specific tasks.
[essential]
(04)
Proven experience in project leading at AI or DeepTech startups / BigTech companies.
[required]
(05)
Designing and deploying RAG-enhanced solutions for enterprise use cases.
[advantageous]
(06)
Open-source projects in the AI/NLP domain.
[advantageous]
(07)
Work experience in startups.
[advantageous]
(08)
Track record of papers accepted for publication in peer-reviewed international conferences and academic journals.
[advantageous]
(09)
Experience in designing / developing dialogue systems.
Technical skills
[essential]
(01)
Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch).
[essential]
(02)
Experience with NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK).
[required]
(03)
Experience in implementing Retrieval-Augmented Generation (RAG) workflows.
[required]
(04)
Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS) and retrieval systems.
[required]
(05)
Ability to design pipelines for document retrieval, indexing, and real-time query response.
[required]
(06)
Experience with chain-of-thought, tree-of-though and other advanced prompting techniques.
[advantageous]
(07)
Knowledge of cloud platforms and MLOps (e.g., AWS, GCP, Azure, or Kubernetes).
[advantageous]
(08)
Ability to integrate language models with external data sources, APIs, and knowledge graphs.
[advantageous]
(09)
Familiarity with optimization techniques for LLMs (e.g., pruning, quantization, knowledge distillation).
[advantageous]
(010)
Experience in combining neural models with symbolic reasoning systems or rule-based approaches.
[advantageous]
(011)
Understanding of ontologies, graph-based representations, and symbolic logic frameworks.
[advantageous]
(012)
Understanding of distributed computing and GPU/TPU acceleration.
Educational background
[advantageous]
(01)
Degrees in Computer Science, Mathematics, Computational Linguistics, or a related technical discipline.
[advantageous]
(02)
Group theory.
[advantageous]
(03)
Montague grammar.
[advantageous]
(04)
Personally implemented a compiler.
Soft skills
[essential]
(01)
Proactive mindset to stay updated with the latest advancements in AI and LLMs.
[essential]
(02)
Fluent in conversational and written business English (C1+).
[required]
(03)
Ability to work collaboratively in cross-functional teams.
[advantageous]
(04)
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.
What we are offering
Competitive Salary
Depending on the candidate's skill level, our target salary range is 14-17M JPY per year for a full-time position and equity compensation (options).
(01)
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
(02)
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.
(03)
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.
(04)
Medical Allowance
Compensation of overseas health insurance and additional medical costs, yearly health checkup.
(05)
Language Courses
Support for English and Japanese language training.
(06)
Other
Visa Sponsorship, Relocation Allowance, Travel Allowance, Monthly commute expense in Japan, Japanese Social Security.
(07)
How we are different
Not just an ML
(01)
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.
Going beyond
(02)
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.
Safety and Alignment
(03)
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.
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© 2025 Noeon Research. All rights reserved.
Midtown Tower 34F, 9-7-1 Akasaka, Minato-ku, Tokyo, Japan
Midtown Tower 34F, 9-7-1 Akasaka, Minato-ku, Tokyo, Japan