Job Description:
Business Overview
AI & Data Division (AIDD) spearheads data science & AI initiatives by leveraging data from the Rakuten Group. We build a platform for large-scale field experimentation using cutting-edge technologies to provide critical insights that enable faster, better business decisions and impact. Our division boasts an international culture shaped by talented employees from around the world. Following the strategic vision, “Rakuten as a data-driven membership company,” AIDD is expanding its data & AI-related activities across multiple Rakuten Group companies.
Department Overview
The GPU Optimization Department (GPUOD) is a core part of Rakuten’s AI & Data Division (AIDD). We accelerate AI workloads by operating and productizing GPU capabilities at scale, serving both internal teams and external enterprise customers.
- Manages thousands of enterprise-grade GPUs
- Provides GPU access for internal teams running training and inference workloads
- Delivers low-latency, cost-optimized Inference as a Service (IaaS), powering Rakuten’s real-time AI applications
- Accelerates LLM adoption by optimizing training, fine-tuning, and serving of large language models across the company
- Productizing our GPU expertise for external enterprise clients
Position:
Why We Hire
As a Product Manager in GPUOD, you will drive product strategy and execution for our internal AI platform and external B2B platform. You’ll own the full product lifecycle—from market research and competitive analysis to roadmap definition, cross-functional delivery, and commercial readiness. You will translate internal customer needs into a clear roadmap, drive cross-functional delivery with engineering teams, and ensure successful adoption through documentation, enablement, and stakeholder alignment.
Position Details
Key Responsibilities
- Product Strategy & Roadmap: Define vision, positioning, and GTM for both internal and external GPU products. Align with Rakuten’s AI ambitions and enterprise customer needs
- Market Research & Competitive Analysis: Identify gaps, benchmark against cloud providers (AWS, GCP, Azure) and niche players, and determine product–market fit
- Requirements & Feature Definition: Gather input from internal ML teams and external enterprise clients to build a robust product backlog
- Cross-Functional Execution: Lead engineering, infrastructure, SRE, and business teams to deliver scalable, reliable, and monetizable solutions
- Commercial Readiness: Own pricing, chargeback, and packaging for the B2B; work with legal, sales, and finance to ensure smooth customer onboarding
- Adoption & Enablement: Drive user adoption through documentation, workshops, and feedback loops; measure success via usage metrics and business impact
Mandatory Qualifications:
- Over 3 years as a Product Manager for infrastructure, AI/ML platforms, or B2B SaaS
- Experience taking 0-to-1 products to market, including competitor analysis and pricing strategy
- Strong ability to translate ambiguous needs into PRDs, roadmaps, and KPIs
- Track record of partnering with engineering, infra teams, and SRE to build scalable platforms
- Data-driven mindset with experience defining and tracking product and business metrics
- Excellent communication skills in a global, cross-cultural environment (English required, Japanese a plus)
Desired Qualifications:
- Familiarity with GPU/AI infrastructure concepts: Kubernetes, Scheduling & multi-tenancy, Inference serving, MLOps
Additional information on English Qualification
Fluent Level English
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