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Role Overview

The AI Engineer (ML Ops Lead) will design, implement, and maintain AI & ML solutions across multiple business areas. The role applies advanced algorithmic, computational, and data exploration skills to deliver scalable, high-performance pipelines and systems. This position leads small projects or segments of large international projects, manages risks in novel situations, and provides technical leadership and mentorship to junior AI engineers.

Responsibilities
・Lead the development and optimization of ML pipelines and highly scalable tools, including rule-based and ML models.
・Architect, implement, and maintain analysis pipelines, ensuring they adapt to evolving business requirements.
・Build and maintain platforms capable of storing and processing large volumes of data efficiently for ML analysis.
・Apply ML / Agentic AI techniques in modern parallel environments (distributed clusters, GPU, multi-core).
・Collaborate with internal teams (IT, business, brand) and external vendors to deliver solutions.
・Manage operational projects, including pipeline maintenance and vendor coordination.
・Ensure quality control, application security, and performance optimization.
・Research market trends and emerging technologies, integrating relevant findings into solutions.
・Perform technical expertise in at least one AI/ML specialization (e.g., graph recommendation, deep learning, NLP, pattern recognition).
・Mentor and train junior AI engineers.
・Communicate AI value and project progress to senior stakeholders.

経験 Experience

<必須 Mandatory>
• At least 5 year of project experience of system integration using ML models.
• Support our business unit through creating analysis pipeline with defined business issue; architect and create pipelineh, maintain and modify existing pipelines to adjust business environment change.
• Develop and maintain analysis platform which stores vast amount of data to provide machine learning (ML) analysis quickly and stably.
• Lead the development and optimization of highly scalable tools leveraging ML and rule-based models.
• Drive the adaption of ML models / Agentic AI to best exploit modern parallel environments (distributed clusters, GPU, multi-core).
• Manage project to deliver pipeline architecture definition; visualize architecture, contextualize system operation flow, create clear documentations, explain the contents of complex analysis system to non-analytical personnel.
• Collaborate with various functions (IT, brand team, external vendors etc.) to propose solutions to business unit.
• Manage operational projects (modify and maintain existing pipelines etc.) with external vendors.
• Ensur quality control, application security, and performance optimization.
• Research market trends and the latest technologies, and apply relevant findings to services.
• Perform technical expertise in at least one AI specialism (graph recommendation, deep learning, natural language processing, pattern recognition etc.).
• Mentor & train more junior AI Engineers.
• Communicate with senior stakeholders to champion the value of AI.

<歓迎 Nice to have>
• At least 5 years of experience in pharma industry or consulting farm.
• Multi-person model development using CI/CD (GitHub, Codecommit etc.)
• Experience in front-end application development.
• Managing customer expectations for projects involving multiple stakeholders.
• Willingness of pushing AZKK’s business by accelerating data-driven decision making.

資格 License

<必須 Mandatory>
• Bachelors Degree or equivalent number of years of experience in Computer Science or a related quantitative discipline.

<歓迎 Nice to have>
• Masters or PhD in computer science or related quantitative discipline.

能力 Skill-set

<必須 Mandatory>
• Leading cross-functional analysis projects communicating with both business and IT infrastructure teams.
• Stakeholder’s expectation management to maximize benefit for both stakeholders and team members.
• Managing project schedule and outcome quality.
• Prioritizing detailed tasks to handle multiple projects with limited resources.
• Designing appropriate ML operation architecture to solving complex business issues.
• Pipeline building by use of (Py)Spark, Python, SQL.
• Data extractions by SQL or other related database management languages.
• AWS services to deploy ML models (SageMaker Studio (notebook, pipeline), EMR, Athena, Glue, CI/CD pipeline, ECR).
• Ability to create documents to clearly explain complex architecture without using language for specialist.
• Understanding business needs and objectives properly.
• Explaining complex analysis to non-analytical personnel.

<歓迎 Nice to have>
• Basic ML knowledge.
• Experience in front-end application development.
• Providing Excel based data aggregation.
• Managing customer expectations for projects involving multiple stakeholders.
• Willingness of pushing AZKK’s business by accelerating data-driven decision making.
• Eagerness to absorb new, cutting-edge methods.
• Good communication and logical thinking skill.

語学 Languages

<必須 Mandatory>
•   Business level proficiency in Japanese and English.