Build AI Worker VoiceAgent’s web frontend, designing visual interfaces and admin features, selecting architecture, and delivering releases with TypeScript and React in a hybrid office/home role.
About this role
CyberAgent's AI Business Unit, a development organisation that is over 70 percent engineers, hires a Machine Learning Engineer for its AI creative products, in particular Kiwami Yosoku TD (Extreme Prediction TD), an AI tool that predicts and automatically generates advertising text. It handles search-linked ads through a trigger mechanism that detects changes, generates ad copy and delivers it, and the team works with the company's AI Lab to improve prediction accuracy and extend to other creative types.
The engineer researches and develops methods that use large language models and other machine learning to generate and evaluate high-quality search-ad copy. That includes studying the ad effect that creative produces, building stronger creative-effect prediction AI, automatically generating better creative and using many kinds of data strategically.
Applicants need five or more years of development in a language such as Python, public cloud experience on AWS or GCP, practical machine-learning service development, data pipeline building and upkeep, team development with three or more people, and the ability to find and propose problems on their own.
This is an AI-generated summary of the employer's original posting — details can be incomplete, out of date or simply wrong. Always confirm everything on the official posting before applying.
Similar jobs
Advise clients on data strategy, build DWH and BI foundations, and use SQL, Python, machine learning and CRM analytics to improve marketing, forecasting and business operations.
Lead requirements definition and delivery of client-specific AI agents for advertising and marketing, coordinating stakeholders and supporting clients’ AI transformation in a hybrid Tokyo role.
Builds the data foundation for an AI and analytics product by matching records, modeling reliable datasets, and improving the quality and consistency of entertainment data.
Design data platforms, models, governance, and knowledge graphs for AI-based financial advice, including architecture, data flows, and continuous learning; remote work is possible weekly.
Learn warehouse-system implementation through configuration, data preparation and testing, then grow into customer requirements, operating design and project coordination.