どんな仕事かAIによる生成

Rakuten MobileのArchitecture Review Boardで、AI/MLのアーキテクチャ設計・評価と、ネットワーク全体のAIガバナンスを担うポジションです。Tech SLMの構築、モデルやAI/MLインフラの評価、設計パターンや監視フレームワークの整備を行います。

応募資格

Bachelor’s degree in Computer Science, AI, Machine Learning, Data Science, Telecommunications Engineering, or a related field.
7+ years of total industry experience.
3+ years of experience in application/software design and architecture with AI/ML, including hands-on Generative AI implementation and model design.
Strong expertise in LLMs/SLMs, fine-tuning techniques, RAG, vector databases, and prompt engineering.
Experience designing and deploying scalable AI solutions using Python, cloud platforms, and Kubernetes.
Solid understanding of AI governance, responsible AI practices, security, and data privacy.
Basic understanding of Telco networks, Cloud, and networking technologies.
Proficiency in English.

Master’s degree in Computer Science, Data Science, or AI/ML fields.
7–15 years of total experience, with at least 3 years in AI/ML design and implementation.
Experience in telecommunications, mobile network architecture, autonomous networks, and related AI use cases.
Hands-on expertise with advanced LLM optimization (LoRA, QLoRA, model distillation) and agentic AI frameworks.
Experience building enterprise AI platforms, AI copilots, or domain-specific language models.
Strong knowledge of MLOps, AI observability, model monitoring, and lifecycle management tools.
Proven ability to establish AI governance frameworks and assess third-party AI vendors.
Relevant certifications (AWS, Azure, GCP, NVIDIA, or equivalent).
Japanese language skills are an additional advantage.

Tech SLM Engineering:** Build the proprietary Tech SLM platform using advanced LLM fine-tuning and high-precision RAG pipelines to automate HLD creation and design reviews.
Strategic AI Governance:** Serve on the AI Council to validate use cases, set standardized design patterns, and enforce network-wide architectural guardrails.
Algorithmic & Model Assessment:** Evaluate open-source or proprietary models against strict telecom network performance, safety, and latency metrics.
ML Infrastructure Review:** Audit and review existing AI/ML infrastructure to provide design optimizations that streamline workloads and significantly reduce infrastructure usage.
Vendor Auditing & Integration:** Scrutinize third-party AI tools and agentic frameworks to ensure secure integration while preventing vendor lock-in.
Architectural Guardrails:** Define standardized architectural disciplines, design patterns, and best practices for AI/ML implementation across the network.
Operational Integrity:** Establish comprehensive monitoring frameworks to track model performance, safety, and data governance.
Ecosystem Integration:** Ensure seamless, secure, and low-latency integration of AI services within the existing Rakuten Mobile network stack.

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