Senior ML Engineer (LLMOps)

Noeon Research Minato-ku, Tokyo June 10 2026
  • 💴 ¥18M ~ ¥21M annually
  • 🏡
    Partially remote
  • 🌏
    Apply from abroad
    Relocate to Japan
  • 💬
    No Japanese required
    Business English
  • 🧪
    Senior level
    3+ years experience required
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About Noeon Research

Noeon Research Minato-ku, Tokyo

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.

Key benefits

  • Competitive salary
  • Flexible schedule
  • High autonomy

About the position

We are looking for an aspiring professional to join our RnD team.

Responsibilities

  • 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.

Requirements

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).

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.

Educational Background

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Engineering, or a related field (or equivalent practical experience).

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 recognize areas for growth and proactively learn new skills 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.
  • 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.

Nice to haves

While not specifically required, tell us if you have any of the following.

  • Experience working in fast-moving startup or R&D-driven environments is a strong plus.
  • Understanding of distributed systems concepts is a plus.

Compensation

¥18,000,000 ~ ¥21,000,000 annually.

Hiring Process

  1. 1

    Initial Screening Interview (45 minutes)

    With either CHRO or Talent Specialist.

  2. 2

    Test Assignment

    This mandatory assignment takes up to 2 hours to complete, within 24 hours from the start, and is unpaid.

  3. 3

    1st Technical Interview with our Tech Lead (1 hour)

    Discuss the test assignment, and check Python proficiency.

  4. 4

    2nd Technical Interview with our LLM Lead (2 hours)

    To check domain specific proficiency.

  5. 5

    Final interview with our CEO (1.5 hours)

    To check values alignment.

APPLY FOR THIS POSITION
DO YOU NEED MORE INFO?
ASK A QUESTION

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