Machine Learning Engineer (New App Development)

Overview

We are building a data platform product for the manufacturing industry, focused on utilizing and structuring complex data such as engineering drawings with machine learning and various technologies. The platform is rapidly expanding within Japan and internationally. We are looking for engineers to join our team to push the limits of manufacturing technology by enhancing our data platform, building new applications, and strengthening our infrastructure.

Role Description

As a Machine Learning Engineer, you will leverage our data assets to explore technologies, design and validate models, and develop robust systems with your team. You will be directly involved in creating business impact through AI and have full-stack exposure, from ideation to production deployment and operations.

Example Tasks

• Prototyping and Proof-of-Concepts for New Products:
  Rapidly execute the following process to reduce technical and use-case uncertainties leading to product implementation:
  • Problem Exploration & Solution Proposal:
    Identify business process challenges in manufacturing, collaborating closely with designers, product managers, and domain experts. Conduct user interviews, uncover issues, and plan technical solutions using tools like LLMs and mathematical optimization.
  • Prototyping & Experimentation:
    Run PoCs using rapid UI tools (e.g., Streamlit); gather real-world feedback, validate effects, and iteratively improve based on user input. Tackle analytical and technical challenges as they arise.

What You’ll Gain

• Industrial Impact:
  Address crucial challenges in manufacturing with AI, working hands-on with user companies to solve real problems.
• Full Stack Skill Growth:
  Experience the complete product development lifecycle: ideation, PoC, production, and operations. Expand your ML, optimization, UX, frontend, backend, MLOps, and LLMOps skills.
• New Product Launch Participation:
  Contribute as an early member of a small, elite team; help shape both the technical strategy and organizational foundations, with future paths like Tech Lead or Manager.

Required Qualifications

• 5+ years of experience in machine learning model and data science development
• Solid understanding of ML, statistics, linear algebra, and computer science algorithms
• Experience solving business problems with ML
• Experience preparing verification/analysis reports for stakeholders
• API development/operations experience using Python, Rust, etc.
• Experience with Google Cloud, AWS, or similar cloud services
• Basic knowledge of Docker/container technologies
• Experience with Git, CI/CD in team development
• Fluent Japanese business communication—reading, writing, speaking (e.g., JLPT N2 or 3+ years in a Japanese work environment)

Preferred Qualifications

• Experience releasing and operating ML models in production
• Product management experience for ML-centric products
• Practical use of numerical optimization for business problems
• Continuous improvement/provisioning of ML/DS models
• Experiment management experience in PoC
• ML project management or ML team leadership experience
• Experience with GPU-based data processing (CUDA, OpenCL, cudf, CuPy, etc.)
• Selecting/building system architecture for services
• Multiple awards in data analysis competitions (e.g., Kaggle)
• Frontend/backend web development experience
• Development/operation experience in distributed processing

Personal Profile

• Resonates with the mission to unlock the potential of the manufacturing industry
• Eager to learn and take on new technologies and fields
• Ambitious about catching up with the latest in ML/MLOps
• Takes ownership and proactively solves fundamental problems
• Thrives in fast-paced, uncertain environments by maintaining a positive and constructive attitude
• Communicates and collaborates with empathy, recognizing context and needs of others

Compensation

• Annual salary: 7,000,000 ~ 12,000,000 JPY (divided monthly)
• Salary review: Twice/year
• Stock option plan

Technology Stack

• Frontend:
  • Language: TypeScript
  • Frameworks: React, Next.js, WebGL, WebAssembly
• Backend:
  • Languages: Rust, TypeScript, Python
  • Frameworks: Rust (axum), Node.js (Express, Fastify, NestJS), Python (FastAPI, PyTorch)
• Infrastructure:
  • Google Cloud, Google Kubernetes Engine, Anthos Service Mesh
• Database/DWH:
  • CloudSQL (PostgreSQL), AlloyDB, Firestore, BigQuery
• API:
  • GraphQL, REST, gRPC
• Monitoring:
  • Datadog, Sentry, Cloud Monitoring
• Environment/DevOps:
  • Terraform, GitHub Actions
• Authentication:
  • Auth0
• Development Tools:
  • GitHub, GitHub Copilot, Figma, Storybook
• Communication:
  • Slack, Discord, JIRA, Miro, Confluence

Working Style & Benefits

• Location:

  • Remote-first
  • Office access available anytime if desired
  • Occasional recommended in-person days/meetings (frequency varies by team)
  • Members living outside the Tokyo area are active, too

• Hours:

  • Flextime (core hours 11:00–16:00)

• Employment Status:

  • Full-time, 3-month probationary period (no change in salary/benefits)

• Vacation:

  • Complete two-day weekends (Sat/Sun), public holidays
  • Annual paid vacation (after 6 months), 3 days special paid leave at joining
  • Summer/winter vacations, caregiving, refresh, and condolence leave

• Allowances & Perks:

  • Commuting allowance (up to 30,000 JPY/month, 60,000 for long-distance)
  • Child allowance (15,000 JPY/month per dependent <18 years)
  • Club, event, and team-building subsidies
  • Engineer-specific server cost subsidy (up to 10,000 JPY/month)
  • Book purchase, external training cost support
  • Parental and caregiving leave, marriage/birth gift money, moving allowance
  • Social insurance, supplied PC, health exams
  • Internal awards/recognition

Selection Process

1. Casual interview (on request)
2. Document screening
3. Technical challenge (coding test online)
   • Focuses on collaborative coding skills rather than just speed/algorithm knowledge
4. HR interview (align conditions, answer questions)
5. Technical interview (engineers)
6. Final interview (CTO)
7. Offer meeting

*Additional interviews may occur depending on circumstances.
*Typical process: ~1 month (can be expedited if needed).

Work Location

• Tokyo, office near Asakusabashi station
  (trial, core work is remote. Office attendance is optional.)

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Unlock the potential of manufacturing — leverage AI to directly tackle real industry challenges, grow as a full-stack ML engineer, and drive the launch of entirely new products.