Adora株式会社のMachine Learning Engineerの求人

AI risk detection is at the heart of everything we do — it's what differentiates Kodomamo from every other parental control app on the market. We are looking for a Machine Learning Engineer to go deeper: sharpen our existing models, expand them to new threat types, and help us extend this technology to protect seniors from fraud.
You will own the full ML lifecycle end-to-end — research, experimentation, training, deployment, and monitoring — working directly with the CTO.

What You'll Do

• Research, prototype, and deploy ML models for detecting risky chat content, inappropriate images, and fraud-linked communication patterns.
• Work with backend and product teams to integrate ML inference into production APIs.
• Build and maintain ML pipelines and data workflows on GCP.
• Monitor model performance and iterate based on real-world feedback.
• Stay current with relevant ML research and adapt promising techniques to our safety use cases.

Tech Stack

• ML: Python, TensorFlow / PyTorch
• Cloud: GCP (Vertex AI, BigQuery, Cloud Storage)
• Infra: Kubernetes

Our Culture

• Small, high-calibre team — average age 26–27, many with overseas study or work experience.
• English is our official working language (Japanese also spoken).
• Fully remote & full-flex — we have a Kinshicho (Tokyo) office, but you can work from anywhere.
• Flat org, low hierarchy — everyone talks directly to the CTO and CEO.
• Serious mission, startup energy — we care deeply about social impact and move fast.

Awards & Partnerships

🏆 Cabinet Secretariat 'IchiBiz Award' — Public Safety Prize
🏆 Aichi Prefectural Police Headquarters Award
🏆 18th Kids Design Award — Special Prize from the Jury Chair
🤝 KDDI — Official app on the U12 Value Plan (since Sept 2025)
🤝 Aichi Nisshin City Board of Education — Kodomamo for School adoption agreement

• 3+ years of professional ML engineering experience, with at least one model in production.
• Proficient in Python and experienced with ML frameworks (TensorFlow, PyTorch, or equivalent).
• Hands-on experience building ML pipelines on GCP or equivalent cloud platforms.
• Ability to communicate technical findings clearly in English (our working language).
• Comfortable in a fast-moving, resource-constrained startup environment.

• Experience with NLP, content moderation, or fraud detection use cases.
• Familiarity with Kubernetes-based model serving.
• Experience with privacy-preserving ML or on-device inference.