仕事内容
仕事内容
Build the full-stack infrastructure that turns ML research into deployed products. This role focuses on creating and maintaining the critical systems that bridge the gap between theoretical machine learning research and production-ready applications.
Key responsibilities include:
- Designing and implementing data pipelines that process, validate, and manage large-scale datasets for ML model training and evaluation
- Developing benchmarking systems to measure model performance, track improvements, and identify bottlenecks
- Building user-facing tools that enable researchers and product teams to interact with and monitor ML systems
- Creating infrastructure for model deployment, serving, and scaling in production environments
- Collaborating with researchers and product engineers to translate research findings into deployable systems
必須スキル
- Strong proficiency in Python or similar languages used for data processing and backend development
- Experience with full-stack development across data pipelines, APIs, and user interfaces
- Understanding of machine learning workflows and the tools commonly used in ML research (TensorFlow, PyTorch, etc.)
- Ability to design systems that bridge research prototypes and production deployments
- Experience with version control, testing, and software engineering best practices
勤務地
- Tokyo, Japan
待遇
- Full-time position
- Language: English
募集背景
Sakana AI is rapidly scaling its ML research operations and needs strong infrastructure engineers to support the research team's productivity and enable the transition from prototypes to production-grade products.