AI Engineering Manager

Job Responsibilities:

• Leadership & Team Empowerment: Lead, mentor, and manage a diverse, high-performing team of engineers, scientists, and researchers. Foster a culture of collaboration, innovation, and growth within the team.
• Cross-Functional Collaboration: Work closely with product, data science, and engineering teams to drive alignment on the AI product roadmap and ensure successful delivery of business outcomes.
• AI Model Development & Deployment: Oversee the end-to-end development lifecycle of AI models, including data collection, labeling, model development, experimentation, training, testing, and deployment into production environments.
• Best Engineering Practices: Ensure that best practices in coding and engineering are maintained, prioritizing a robust, scalable, and efficient codebase.
• Pipeline & Experiment Management: Develop, maintain, and optimize AI model training pipelines and experiment tracking systems. Ensure the seamless flow of data through the system and timely feedback on model performance.
• Operational Excellence: Manage the deployment, scaling, and maintenance of AI models in production, working to ensure the systems are reliable, scalable, and continuously optimized.

Required Qualifications:

• 3+ years of experience in managing teams of engineers, scientists, or researchers, with a strong track record of driving successful AI projects.
• Hands-on experience in designing, implementing, and deploying machine learning models in production environments, with a focus on business applications.
• Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams and business leaders.
• Proficiency in modern software engineering practices, including writing clean, maintainable, and well-documented code.

Desired Qualifications:

• Practical knowledge of MLOps principles and technologies (e.g., model versioning, deployment at scale, containerization, continuous integration/delivery).
• Familiarity with cloud platforms (e.g., AWS, Google Cloud) and container orchestration tools (e.g., Kubernetes, Docker).
• Experience with Python (e.g., FastAPI, PyTorch, and related libraries), and modern database systems (e.g., SQL, NoSQL).
• Experience in building and optimizing large-scale data pipelines and AI model training systems.
• Knowledge of the Japanese language is a plus.

Team Culture & Expectations:

• Collaboration: We emphasize teamwork, and engineers are expected to collaborate effectively across functions, sharing knowledge, and empowering each other.
• Ownership & Accountability: Engineers are encouraged to take ownership of their projects, ensuring successful delivery while being proactive about resolving challenges.
• Innovation & Experimentation: Engineers have the opportunity to experiment with new technologies and ideas, contributing to continuous innovation and improvements in our AI models and products.
• Quality: We maintain a high standard of code quality, always striving for excellence and continuous improvement. Engineers are expected to deliver reliable, high-performance solutions.
• Customer-Focused: We value both internal and external customers. Engineers should prioritize delivering value to end-users while also supporting colleagues and contributing to the broader company mission.