AI / Machine Learning Engineer

Are you an AI/ML engineer eager to build production-grade agentic systems and high-impact recommendation algorithms? A fast-growing global travel technology company is looking for an AI / Machine Learning Engineer to help rebuild and scale conversational systems into autonomous AI agents and optimize core machine learning engines.

In this role, you will work across a modern GCP cloud stack, co-developing production microservices, training both LLMs and traditional ML/DL models, and shipping solutions directly to production.

Key Responsibilities

Train, fine-tune, and optimize both LLM and traditional ML/DL models, deploying them to production and owning their reliability, uptime, and performance metrics. Agentic AI & Algorithm Evolution: Build and evolve autonomous AI agents that handle multi-step actions and complex guest inquiries, alongside core recommender systems.

System Evaluation & Testing: Rigorously evaluate AI systems to ensure accurate, reliable end-user outcomes and transparent reporting of capabilities and edge cases. Data Pipeline Engineering: Build robust data pipelines in Big. Query using dbt to support data modeling and model training workflows. Inference Analysis & Experimentation: Analyze model inference results and customer data patterns to design and run tests measuring algorithm improvements.

Cross-Functional Collaboration: Partner closely with backend engineering teams to co-develop microservices and align with product managers on technical strategy.

Requirements

4+ years of combined experience as a Full Stack Data Scientist, Machine Learning Engineer, or AI Engineer. ML & LLM Development: Strong foundation in statistics and machine learning, with proven experience building LLM solutions (e.g., Lang. Chain, Google ADK). Production Coding: High proficiency in Python adhering to software engineering best practices for production deployments.

Data Pipelines & SQL: Solid experience with SQL, schema design, and orchestration tools such as dbt, Airflow, or Prefect. Language Skills: Professional fluency in English. Nice-to-Have Experience designing and evaluating agentic architectures (tool/function calling, guardrails, multi-step workflows). Hands-on work with vector embeddings and RAG pipelines.

Familiarity with LLM observability and evaluation tools (Lang. Smith, Langfuse, Braintrust, or custom harnesses). Japanese language capability.

Benefits

Tokyo, Japan. Work Model: Hybrid working schedule (2 days/week in-office). Employment Type: Full-Time (正社員).

Benefits

Full Japanese social insurance (health, pension, employment, workers' comp) and commuting allowance. Paid Leave: 10 paid leave days granted upon joining, standard weekends/holidays, and year-end/New Year vacations (Dec 29 – Jan 3). Interested in building next-generation AI agents?