AI Engineer

This AI Engineer role is part of a custom AI solutions business. The engineer researches and devises solutions to client challenges using statistical and machine-learning methods, then implements and evaluates those solutions. Responsibilities also include explaining technical progress and discussing technical matters in client meetings, working with solution architects to advance projects, and helping lead technology proposals, agreement-building, implementation, and delivery.

Projects may cover AI utilization consulting, AI system proposals, proofs of concept, prototypes, and system development. Other areas include satellite-data advisory and analysis services, AI analysis engine development, MLOps, continual-learning environments, and additional training support. Projects can cross industries and may involve manufacturing DX, image data, satellite data, sensor data, and other operational AI applications.

The expected experience level is approximately three or more years. Required qualifications include knowledge of deep learning, statistical methods, and machine-learning methods; experience using development tools such as GitHub; the ability and demonstrated experience to implement machine-learning methods with libraries or open-source software; prior-research investigation skills; logical thinking; and the ability to explain complex subjects. Japanese at business level or above and English at conversational level or above are required.

Knowledge of or experience with LLMs and generative AI, image processing, mathematical optimization, or reinforcement learning is welcomed. Cloud knowledge or development experience with AWS, GCP, or Azure, along with general data-analysis and data-science skills, is also welcomed. Interest in taking on project-management responsibilities and participating in engineering recruiting or study-session presentations is noted as a preferred mindset.

The main programming language is Python. The environment includes AWS, GCP, and Azure cloud services, company servers for on-premises work, Git and GitHub for version control, GitHub Actions for CI/CD, Docker for containers, Terraform and AWS CDK for infrastructure configuration, Google Drive for documents, and Slack for communication.

The work location is in Otemachi, Chiyoda-ku, Tokyo. Office attendance is generally once a week, with remote work available according to work circumstances and when compatible with client visits or field surveys.

A buddy system, technical-advisor interaction, and regular study meetings are also provided. Side jobs may be permitted under conflict-of-interest, confidentiality, and performance conditions. An indoor smoking room is provided.