Director - Product Management - Inference as a Service (IaaS)

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July 6

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Mara

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Innovative, aesthetic and functional furniture elements and systems for office, community and everyday life.

11 - 50 employees

📋 Description

• MARA is seeking a Director of Product Management to lead the strategy, development, and deployment strategy for our IaaS platform. • You'll bridge technical, operational, and customer-facing teams to build scalable inference infrastructure that supports real-world AI applications. • Your focus will be on enabling clients to deploy and scale ML models on dedicated compute with maximum performance and uptime. • Define and drive the product vision and roadmap for our Inference as a Service offering. • Gather and prioritize customer requirements from AI developers, enterprise users, and internal stakeholders. • Collaborate with engineering, data center ops, and energy teams to ensure the compute infrastructure meets IaaS needs (e.g., GPU availability, latency targets). • Work closely with sales and business development to support customer onboarding and ensure alignment with SLAs. • Identify market trends, emerging AI inference patterns (LLMs, vision, etc.), and integrate them into product strategy. • Define product KPIs, collect usage data, and iterate quickly based on performance insights. • Ensure the IaaS platform meets compliance, cost-efficiency, and environmental goals.

🎯 Requirements

• 8–12+ years of product management, ideally in data infrastructure, cloud services, or AI/ML domains. • Strong technical understanding of ML inference workloads and GPU/accelerator environments. • Proven experience launching infrastructure products or platforms used by technical teams. • Excellent communication and stakeholder management skills across engineering and non-technical functions. • Experience with tools like Kubernetes, Triton, or model-serving platforms is a plus. • Direct experience in Bitcoin mining or high-performance computing (HPC) environments. • Familiarity with immersion cooling systems, phase-change materials, or liquid-cooled infrastructure. • Experience with SCADA, PLCs, or other industrial monitoring and automation platforms. • Strong knowledge of energy infrastructure, including transformers, switchgear, and power delivery to edge computing sites.