[Why Solafune] Solafune is building the "Planetary Intelligence OS" — transforming satellite and geospatial data into actionable intelligence for defense, national security, infrastructure monitoring, environmental protection, and disaster response. We work directly with government agencies and private-sector partners on problems that matter, and we collaborate with a global community of data scientists through our competition platform to push the frontier of geospatial AI. If you want your work to have real-world, high-stakes impact — not just incremental product metrics — this is that kind of role. [The Role] As an AI Engineer, you will design, develop, and deploy machine learning and deep learning models across diverse data types — imagery, time-series, and natural language. You'll own the full lifecycle from technical proof of concept to production deployment, and you'll also help shape Solafune's AI capabilities by planning and operating data science competitions and evaluating emerging technologies for real-world application. You'll work closely with our research team, product engineers, and clients to bring cutting-edge AI into production — not just into a paper or a notebook. [What You'll Do] - Design, develop, and tune AI models (classification, detection, generation, time-series prediction, optimization) - Implement, train, and evaluate deep learning models in Python using PyTorch / TensorFlow - Handle data preprocessing, feature extraction, and evaluation metric design across image, numerical, and NLP data - Deploy models as APIs and operate them on AWS / GCP / Azure - Plan and run data science competitions — defining problems, preparing datasets, and designing evaluation criteria - Drive projects from PoC through to production implementation - Validate and implement new technologies and algorithms in collaboration with the research team

- Experience developing AI/ML models using Python - Experience building and training deep learning models with PyTorch or TensorFlow - Solid understanding of machine learning fundamentals and model evaluation - Experience with team-based development using Git - Business-level English (must be able to communicate effectively in English)

- Medal-winning track record on Kaggle (Master tier or above) or other global data science competition platforms - Experience building training/inference environments on cloud platforms such as AWS or GCP - Experience with inference optimization using Docker, CUDA, or TensorRT - Experience developing NLP applications (e.g., LLMs, RAG) or generative imaging models (e.g., Diffusion Models) - Hands-on experience with OpenCV, NumPy, Pandas, FastAPI, or Flask - Experience reproducing and applying findings from academic papers - Experience applying AI/ML to satellite or aerial/UAV (drone) remote sensing data - Experience planning and operating competitions or events - Business-level Japanese or proficiency in other languages

Our ideal candidate has hands-on experience with: - Languages: Python, Shell - Frameworks: PyTorch, TensorFlow, FastAPI, Flask - Tools: Docker, GitHub, AWS (EC2, S3, Lambda, SageMaker), GCP - Libraries: OpenCV, NumPy, Pandas, Torchvision, Transformers - Project Management: GitHub, Jira - Internal Communication: Slack, Discord, Notion, Zoom