Platform Software Engineer
Our client works to solve social issues in many industries across Japan. For example, patient care for healthcare providers, resource management for nursing homes, and AI-based quality care for the injured and elderly.
As a software engineer, you will be responsible for designing and implementing software to easily deploy and deliver machine and deep learning assets developed by ML engineers as scalable web APIs. You will also be responsible for the code reviews of your team members and providing guidance.
The platform product strategy is determined by team discussions based on the feedback from the platform users and input from other stakeholders. You will be expected to contribute to the team decision from the viewpoint of a software engineer.
Our client has one of Japan's largest platforms for creating solutions through AI & DX, providing solutions to more than half of Japan's top 100 companies.
9:00–18:00, Monday to Friday (Core time: 11:00 – 14:00)
Saturday, Sunday, and National Holidays, Year-end and New Year Holidays, Paid Holidays, Other Special Holidays
【Services / Benefits】
Social insurance, Transportation Fee, No smoking indoors allowed (Designated smoking area), etc.
- Development experience utilising AWS or other cloud platforms
- Experience in software development projects
- Experience with source control management systems (SCM) and CI/CD
- Effective interpersonal and communication skills (Business-level English and conversational Japanese OR Business-level Japanese and at least reading and writing capabilities for English)
- Experience designing and implementing scalable processing infrastructure utilizing distributed processing infrastructure (Kubernetes/Hadoop, etc.)
- Practical experience in SRE and system operation
- Background in computer science or a related field
- Project management skills
- Product and service development experience
- Experience working in a startup environment
- Understanding of machine learning frameworks (Scipy/Numpy, Scikit-Learn, Pandas, Tensorflow/Keras/PyTorch)
- Understanding of machine learning models in a business environment (linear regression, ensemble learning, boosting, RNN, CNN, GCN, GAN, etc.)
- Strong initiative in a business setting to lead a team/organization