Lead and empower a diverse team of ML engineers and researchers to accelerate machine-learning solutions for business problems. Foster team development and maintain organizational health. Contribute to the product roadmap and technical execution.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
About the Company
Founded in 2014, this Tokyo-based AI startup has been at the forefront of AI innovation, evolving from document processing expertise to full workflow automation solutions. By combining cutting-edge AI with operational automation, the company enables businesses to extract critical information and trigger automated actions, driving efficiency and productivity.
The company culture emphasizes ownership, collaboration, and meritocracy, with high standards for technical excellence and ample opportunities for engineers to propose, own, and lead projects.
Job Title: Machine Learning Engineering Manager
Job Summary
The ML Engineering Manager will lead and empower a diverse team of ML engineers and researchers, accelerating the creation and deployment of machine-learning solutions for real-world business problems. Reporting directly to the CTO, the manager will contribute to the product roadmap, guide technical execution, and foster team growth.
Responsibilities
- Lead and mentor a diverse team of ML engineers and researchers toward individual and collective goals.
- Foster team development and maintain organizational health.
- Collaborate with cross-functional teams to drive the product roadmap.
- Contribute to the full ML model lifecycle: data collection, labeling, model development, experimentation, training, testing, and production deployment.
- Ensure good coding and engineering practices to maintain a clean and maintainable codebase.
Required Qualifications
- 3+ years managing engineers, researchers, or scientists.
- Professional experience designing, implementing, training, and deploying ML models for business applications.
- Excellent collaboration and communication skills across departments and leadership levels.
- Business-level proficiency in Japanese and English.
Preferred Qualifications
- Knowledge of MLOps principles and DevOps practices (model/data versioning, large-scale model training and serving).
Tech Stack
- PyTorch, Docker, Knative, Kafka, Kubernetes, Nvidia Triton
- Cloud: Google Cloud Platform, AWS
- CI/CD: GitHub Actions
What We Offer
- Competitive salary and biannual performance bonuses
- Stock options
- Visa sponsorship (if required)
- Subsidized language training and gym membership
- Free in-office breakfast, coffee, tea, snacks
- Commuting allowance and full Japanese social security benefits
- Paid holidays up to 20 days/year, plus bereavement/congratulatory leave
- Maternity/childcare leave (for all genders)
- Annual health checkups
Working Conditions
- Full-time, permanent position based in Minato-ku, Tokyo
- Working hours: 9:00 a.m. – 6:00 p.m., 1-hour lunch break
- Holidays: weekends, national holidays, year-end/New Year holidays
- 3-month probation period