Machine Learning Engineer

📍 Tokyo

Hybrid: 1 to 2 days on site

Client Overview

We are working with a global knowledge-sharing and expert network company that connects organizations with industry professionals to provide specialized insights for strategic decision-making. The company supports leading consulting firms, investment organizations, and enterprises worldwide, leveraging technology to make expert knowledge more accessible, efficient, and impactful.

They are looking for a Machine Learning Engineer who can build and scale production AI systems, including machine learning models, AI agents, and LLM-based applications. The role involves designing, fine-tuning, deploying, and optimizing models across platforms, while applying strong MLOps practices around CI/CD, monitoring, and model lifecycle management.

Required Qualifications

◎ Production ML & Backend: Hands-on experience building and operating production-grade backend services and ML pipelines, not just research/prototypes:

• Mid-level: 3 years, with the ability to independently navigate and contribute to large, multi-module Python codebases.
• Senior-level: 5 years, with demonstrated experience architecting event-driven workflows, optimizing system latency, and designing hybrid search/retrieval systems.

◎ LLM / GenAI: Practical experience with LLM orchestration, including structured outputs, tool/function calling, and multi-step agent workflows.

◎Tabular ML: Hands-on experience with feature engineering, ranking models / Learning-to-Rank (LTR), and model validation.

◎ DevOps / MLOps: Experience with Docker, pytest/mocking, and CI/CD

If you’re considering a new career move and are highly autonomous, comfortable collaborating with global engineering teams, and interested in taking end-to-end ownership from problem definition through product delivery and continuous improvement, this is definitely a role worth exploring.