Applications: candidates may apply from outside Japan. Visa sponsorship: available. Japanese: Not required. English: Business level. Japan Dev tags: Engineering, ML, Python, Kubernetes, Docker, Deep Learning.
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.
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.
Nice to haves
- Experience working in fast-moving startup or R&D-driven environments is a strong plus.
- 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).
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
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Individual responsibility. You respect key deadlines and pass on the results of your work to your teammates in an appropriate condition.
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Lifelong learning. You recognize areas for growth and proactively learn new skills for your current and prospective areas of responsibility.
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Vision & planning. You can plan your work several weeks ahead and can juggle multiple projects at once. You know when to postpone a task.
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Thoroughness. You cover every important aspect of your task leaving out no crucial detail.
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Proactiveness and initiative. You offer help if you have spare capacity. You take initiative and pitch your own projects to others.
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Critical thinking. You question every judgement, claim or number and can engage in a healthy debate with your teammates.
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Dynamic, out-of-the-box mindset. You can challenge existing ways, abandon well-trodden paths and embrace the new.
Hiring process steps
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Initial Screening Interview (45 minutes)
With either CHRO or Talent Specialist.
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Test Assignment
This mandatory assignment takes up to 2 hours to complete, within 24 hours from the start, and is unpaid.
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1st Technical Interview with our Tech Lead (1 hour)
Discuss the test assignment, and check Python proficiency.
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2nd Technical Interview with our LLM Lead (2 hours)
To check domain specific proficiency.
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Final interview with our CEO (1.5 hours)
To check values alignment.