🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
＜Summary＞ Position: AI Engineer Salary: ￥6M～￥15M Location: Full remote [Company Profile] We are an AI startup originating from the Matsuo Lab at the University of Tokyo. With a mission to "create the new standard in uncharted territory," we have established a leading track record in Japan for the real-world implementation of Large Language Models (LLMs). Following a capital and business alliance with the KDDI Group, we are currently in a phase of rapid growth, deploying AI products—such as "ELYZA Works"—to a wide range of companies. [Job description] As a Machine Learning Engineer on the product team, you will be responsible for developing products centered around LLMs (proprietary/in-house models). - Leverage ML technologies, including LLMs, to solve problems and create value for our products. - Take ownership of establishing internal systems that integrate machine learning and engineering. - Address technical debt to ensure sustainable development. - Develop and operate scalable, highly available LLM inference infrastructure. 【Job Overview】 1. Product Development - Handle the end-to-end process for ML-powered features, from requirements definition and value validation to development. - Drive continuous improvement based on user feedback and quantitative metrics. - Optimize in-house models and integrate them into products. ∟ Optimize models by balancing inference speed and accuracy. ∟ Research and apply model lightweighting techniques. 2. Leading ML & Engineering Integration - Implement internal libraries to facilitate the integration of ML models into products. - Establish workflows for efficient production deployment of models. - Optimize and refactor product code. - Provide technical support to other teams (consulting on architecture and implementation strategies). 3. MLOps Infrastructure Development & Improvement - Design and implement scalable, flexible inference infrastructure. - Build systems for continuous model monitoring and performance evaluation. - Establish best practices for model operations in production environments. ▼Development Environment We fully utilize cutting-edge AI development tools—such as Claude Code and Devin—while maintaining a strong focus on security. - Languages: Python - Cloud Platforms: Google Cloud / AWS / Azure - Provisioning Tools: Terraform - CI/CD: GitHub Actions / Argo CD - Middleware: OpenSearch - Documentation: Notion / Google Docs - Development Tools: GitHub / Figma - Communication Tools: Slack / Discord / Google Meet - BI Tools: Redash [All of the following are required] - 2+ years of experience developing and operating ML services within a team - Experience with development and operations in cloud environments such as GCP or AWS - Expertise in one of the following fields: Machine Learning, Natural Language Processing, Image Recognition, or Speech Recognition - Business-level Japanese communication skills / Native-level Japanese proficiency *Please submit a portfolio, such as a GitHub account. [Conditions] Employment Type: Permanent Estimated annual income: ￥6M～￥15M ◆ 120 annual holidays (FY2025) ◆ Full two-day weekend/holiday schedule (Saturdays, Sundays, and national holidays off) ◆ Year-end and New Year holidays ◆ Paid leave (granted upon joining; number of days depends on the month of hire) ◆ Pre- and post-natal leave ◆ Childcare leave ◆ Bereavement and special occasion leave
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.
