AI / Machine Learning Engineer
AI/ML engineer at a fast-growing global travel tech company in Tokyo: training and fine-tuning LLM and traditional ML/DL models, building autonomous agentic systems and recommender engines, creating BigQuery/dbt data pipelines, and co-developing production microservices on GCP. Full-time, hybrid with 2 days/week in office.
- Compensation
- Not disclosed
- Location
- Tokyo, Japan
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Full time
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Must have
- 4+ years combined experience as a Full Stack Data Scientist, Machine Learning Engineer, or AI Engineer
- Strong foundation in statistics and machine learning
- Proven experience building LLM solutions (e.g., LangChain, Google ADK)
- High proficiency in Python adhering to software engineering best practices for production deployments
- Solid experience with SQL and schema design
- Experience with orchestration tools such as dbt, Airflow, or Prefect
- 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 (LangSmith, Langfuse, Braintrust, or custom harnesses)
- Japanese language capability
Full description
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
- Model Training & Production Deployment: 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 BigQuery 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
Key Requirements
- Professional Experience: 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., LangChain, 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 (LangSmith, Langfuse, Braintrust, or custom harnesses).