English speaking AI/Machine Learning Engineer (Full Remote UP to 12M)
- Hiring from
- Japan
- Work type
- Remote
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AI/Machine Learning Engineer (Remote)
Want your models to be used by real people every day, not parked in a notebook? We’re a fast-growing travel tech company building products that help hotels around the world run smoother, serve guests better, and grow sales. Our data team is hiring AI/ML Engineers to build what comes next.
Location: you must be based in the Kanto area. Our office is in Nishi-Shinjuku, Tokyo, and remote work is OK.
Who we build for
Our clients are hotels, and their guests are the end users of what you’ll build. Thousands of hotels around the world use our products, so your work runs in real hotel operations, not in a lab.
- Guests meet our work on official hotel websites, where recommenders pick the room plans they see, and through a chat agent that answers their questions
- Hotel staff rely on the agent to handle guest questions and take actions for them, so accuracy and reliability matter
- Hotels use our tools to streamline processes, deliver high-quality guest service, and drive sales growth
What you’ll be working on
Two big areas define our work right now, and both are consumer-facing products at scale:
- Recommender systems: our biggest revenue driver. They show guests the most relevant room plans on official hotel websites.
- An AI agent: we’re rebuilding a chatbot used by thousands of hotels into an agent that accurately answers guest questions and takes actions on behalf of hotel staff.
There’s a lot of greenfield work, and you’ll have the freedom and ownership to choose how you build it.
What you’ll do
- Evaluate AI systems so accurate, reliable results reach end users, and report openly on what they can and can’t do
- Train and improve LLM and traditional ML/DL models, deploy them to production, and co-own their reliability, uptime, and performance
- Analyze customer data and model outputs to find patterns, and run tests to measure the impact of your improvements
- Build data pipelines in BigQuery with dbt to support your own model development
- Explain what you’re building, and why it matters, to product managers and business stakeholders
What we’re looking for
Must-haves
- At least 2 years of experience developing production ML and/or AI services
- Experience on a user-facing product with a high volume of requests, where you had to understand and model human behavior and preferences to be effective
- Solid software engineering fundamentals (Python, testing, code review, CI/CD)
- Experience evaluating model quality with sound methods (offline metrics, A/B tests)
- Strong SQL and data pipeline skills
- Fluent English
- Based in the Kanto area
Strong plus
- Experience with consumer-facing AI chatbots, recommender systems, or dynamic pricing, coupon, and marketing-points campaigns
- At least 1 year at a large, well-known web services company (e-commerce, fintech, or similar)
- Ability to read Japanese (or at least kanji) is a plus
- A master’s degree in a related field (not required)
- Experience with LLMs and agents, GCP, BigQuery, dbt, or microservices
You’ll thrive here if you…
- Are motivated by big, impactful projects that get released in production
- Care more about the effect on users and the business problem than the uniqueness or academic value of the algorithm
- Ask questions, give feedback, and disagree with executives when you see things differently
- Are passionate about good systems and processes for engineering
Why you’ll love it here
- Real impact at scale: your work drives our biggest revenue line and a flagship AI agent used by thousands of hotels
- Greenfield problems and real ownership: you choose how to solve them and you own the result in production
- Strong engineers around you: a modern GCP stack, a focus on fundamentals, and close work with backend, product, and data colleagues
- Flexibility: remote work is OK, with a Nishi-Shinjuku office when you want to collaborate in person
- Room to grow, with salary increases and promotions available
- Weekends off, with a 10:00–19:00 schedule that leaves your mornings free
