1. Business Strategy & Contribution
- Strategic Roadmap: Develop and communicate the mid-term AI strategy roadmap, ensuring full alignment with the company's overall business objectives.
- Product Alignment: Define and drive the technical roadmap for AI systems, bridging the gap between technical capabilities and product goals.
- Collaboration & Planning: Partner with the Product Design (PD) team for seamless planning and operation.
- Identify key functions and quality standards during the product OKR planning process.
- Technical Evangelism: Explain complex technical aspects to business stakeholders to ensure transparency and informed decision-making.

2. Technical Leadership & System Architecture
- Solution Design: Lead the AI team in designing, developing, and deploying high-impact solutions for Computer Vision and OCR/Document Understanding problems.
- Scalable Infrastructure: Architect and implement end-to-end scalable AI pipelines, including:
 + Data ingestion and preprocessing.
 + Model training, evaluation, and experiment tracking.
 + Deployment, monitoring, and continuous improvement.
- Core Development Oversight: Oversee the development of Object Detection models, AI-powered search/retrieval systems, and (optional) 3D recognition technologies.
- Engineering Excellence: Enforce high-quality engineering practices, including rigorous code reviews and ensuring reproducibility.
- Stay at the forefront of advancements in AI, Computer Vision, and Deep Learning to evaluate their applicability to the product.
- Cross-functional Integration: Work closely with Backend Engineers (API, Microservices) and Product teams to handle requirements and prioritization.

3. Team Management & Operations
- Workflow Management: Operate and optimize team workflows based on established rules and regulations to improve productivity.
- Governance & Transparency: Maintain absolute transparency in operations through regular reporting and obtaining necessary approvals from superiors.
- Establish and strictly enforce confidentiality mechanisms and data security protocols.
- Mentorship: Guide and mentor junior AI engineers, fostering a culture of technical growth, best practices, and innovation.

Language Skill: Good Communication in English or Japanese
Computer Skill: programming such as Python, Java,.....
Working Experience: 5 year+

Must Requirements:
- 5+ years of industry experience in AI, Machine Learning, or Deep Learning, with at least 1-2 years in a leadership or ownership role.
- Strong hands-on experience in Computer Vision, especially:
 + Object Detection (YOLO, DETR, etc.)
 + OCR/document understanding (PaddleOCR, Tesseract, VLMs, etc.)
- Proficiency in deep learning frameworks such as PyTorch or TensorFlow.
- Solid experience in designing and deploying AI systems into production environments (real-time or batch).
- Model optimization (latency, throughput, memory)
- Data pipelines and feature engineering
- Experience working with:
 + Large-scale datasets
 + SQL/NoSQL databases
- Strong programming skills in Python (and system-level thinking for production code).
- Experience collaborating with cross-functional teams (Backend, Data Engineering, Product).
- Ability to lead technical direction, break down complex problems, and guide execution.
- Strong problem-solving mindset with ability to operate independently and make decisions under ambiguity.

Preferable Skills:
- Academic background in AI, Machine Learning, Computer Vision, or related fields.
- Experience with 3D vision/CAD-based AI/point cloud processing.
- Familiarity with search/retrieval systems: Elasticsearch, Solr, FAISS, vector search
- Experience with Vision-Language Models (VLMs) or multimodal AI systems.
- Hands-on experience with model optimization frameworks: TensorRT, ONNX, quantization, pruning
- Experience deploying AI systems on cloud platforms (AWS, GCP, Azure) or hybrid/on-prem setups.
- Understanding of MLOps/CI-CD pipelines for model lifecycle management.
- Experience in manufacturing/technical drawing/industrial AI applications is a strong plus.
- Experience mentoring or managing junior engineers.

* Salary increase: Once a year
* Bonus: Depending on work performance and business result 
* Others: Hybrid 
* Benefits:
   - Company-provided laptop. 
   - Annual health check-up (once per year). 
   - 12 days of annual leave. 
   - Full salary-based social insurance contribution. 
   - Opportunity to work in an international environment and develop foreign language skills (English, Japanese). 

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