English summary for screening — check the original posting before applying.
Athena Technologies is seeking a Machine Learning Engineer to develop and implement AI systems for client business challenges, focusing on private AI construction. This role is for individuals who want to balance work with research, childcare, or caregiving, while continuing to engage in AI development as a full-time employee. Despite reduced working hours, you will be responsible for a defined scope within projects, contributing clearly and achieving results.
Must-haves
- Experience in research or development using Machine Learning or Deep Learning
- Implementation experience with Python, PyTorch or TensorFlow, Scikit-Learn
- Ability to independently design, implement, and verify your area of responsibility
- Team development experience using Git, GitHub, etc.
- Ability to manage priorities and progress within limited working hours
- Ability to perform necessary communication and handovers without relying on overtime
Nice-to-haves
- Experience in developing and operating ML models in products
- Research or implementation experience with Generative AI/LLM
- Experience with image recognition, mathematical optimization, time-series forecasting, or demand forecasting
- Experience deploying and operating models in cloud environments (AWS, GCP, etc.)
- Development experience integrating with APIs, backends, and data infrastructure
- Experience operating models using MLOps tools
- Experience in technical leadership, code reviews, and design reviews
- Experience organizing requirements and explaining technology to clients
- Experience balancing work with research, childcare, or caregiving
Tech stack
PythonPyTorchTensorFlowScikit-LearnGitGitHubAWSGCPGenerative AILLM
Work style
Hybrid/Remote work is possible. Flexible work styles are encouraged. Location: Kyoto.
Other notes
Reduced hours full-time position. Salary is calculated proportionally to full-time salary (annual salary range for full-time: JPY 7,200,000 - 12,000,000) based on working hours (e.g., 80% for 32 hours/week, 60% for 24 hours/week). Actual salary depends on experience, skills, role, and agreed working hours. Probationary period: 3 months.