Generative AI Machine Learning Engineer

This machine learning engineer will help launch and improve new products that use generative AI for pharmacy-focused SaaS products, including Musubi, Pocket Musubi, Musubi Insight, and Musubi AI Inventory Management. The work includes several generative-AI enhancement projects for existing products and future use-case projects intended for practical social implementation and patent development.

Day-to-day responsibilities include defining problems, running experiments, and evaluating use cases involving natural language processing such as speech recognition and structuring. The engineer will design and implement product functionality and experimentation infrastructure, analyze product usage data to identify issues and propose improvements, and plan and validate ideas for patent applications.

Because the products support core pharmacy operations, the role requires balancing multiple aspects of quality rather than focusing only on model accuracy. These aspects include cost, speed, security, reliability, and AI safety.

The position is part of the generative-AI research and development team in the Data & AI area. The team consists of one engineering manager, one data scientist or machine learning engineer, four software engineers, one product manager, and one pharmacist serving as a domain expert. Internal counterparts include product management, customer success, site reliability engineering, and data reliability engineering teams.

The stated development technologies are React, Hono, TypeScript, Python, AWS Glue, Athena, ECS Fargate, SageMaker, Lamdba, and CDK, along with Azure OpenAI Service, GCP VertexAI, and Databricks. The listed large language model services are OpenAI, Gemini, and Claude through Amazon Bedrock. AI software services include GitHub Copilot, Dify, Cursor, Devin, and NotebookLM.

The company also describes cross-functional generative-AI knowledge-sharing activities involving engineers, product managers, and designers. Internal guidelines address security risks associated with handling responsible medical information. The listed work location is in Tokyo at 105-0003, 東京都港区西新橋2-8-6 住友不動産日比谷ビル5F.

The stated selection process includes document screening, a casual interview, three to four interviews, an aptitude test, a reference check using back check, and an offer meeting. The process may change depending on circumstances.