Product Manager – AI Inference, Model Serving

🕒 May 28

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Logo of Mirantis

Mirantis

501 - 1000 employees

🏢 Enterprise

☁️ SaaS

Cloud Computing • Enterprise • SaaS

Mirantis is a company that specializes in container management and cloud infrastructure solutions. It offers a range of products, including Mirantis Kubernetes Engine (MKE), Mirantis OpenStack for Kubernetes (MOSK), and Mirantis Container Cloud (MCC), which provide enterprise-level Kubernetes and container management platforms. Mirantis also develops tools for secure software supply chains, such as the Mirantis Container Runtime (MCR) and Mirantis Secure Registry (MSR). As an advocate for open source technologies, Mirantis supports various projects and provides resources like Lens Desktop, a popular Kubernetes IDE, and technical support for enterprises adopting cloud-native technologies. Their solutions cater to sectors such as public services, financial services, and broader SaaS and technology services industries.

📋 Description

• Own product strategy, roadmap, and lifecycle for inference and model serving, including serverless inference, dedicated endpoints, autoscaling, routing, KV cache management, and the related observability • Lead deep technical discovery with NeoClouds, sovereign clouds, and enterprise platform teams, and translate findings into prioritized requirements and architecture direction • Partner with engineering on system design trade-offs across runtime integration, GPU scheduling, network, storage, and serving topology, including disaggregated serving and multi-model serving • Define positioning grounded in measurable outcomes: latency distributions, throughput per GPU, utilization, tail reliability, and cost per tokens • Drive go-to-market execution: pricing and packaging, reference architectures, sizing guides, PoC playbooks, and direct engagement with customers, analysts, and ecosystem partners

🎯 Requirements

• 7+ years in product management, technical product management, or a senior technical role owning AI/ML and inference product(s) • Strong understanding of production AI inference, including model serving, serverless execution, dedicated endpoints, autoscaling, routing, workload placement, observability, and reliability • Proven capability to reason about performance trade-offs across GPU, network, storage, orchestration, and runtime layers, and to translate low-level technical capability into business value such as TTFT, throughput per GPU, and TCO • Working knowledge of modern inference runtimes (vLLM, SGLang, TensorRT-LLM, Dynamo, Triton) and the optimization patterns that matter in production: continuous batching, KV cache management, cold starts, prefill versus decode, disaggregated serving, and multi-model serving • Credibility with engineering leaders and infrastructure operators, including comfort in production architecture reviews and technical commercial conversations with platform engineering buyers.

🏖️ Benefits

• Work with an established Silicon Valley leader in the cloud infrastructure industry. • Work with exceptionally passionate, talented and engaging colleagues, helping Fortune 500 and Global 2000 customers implement next-generation cloud technologies. • Be a part of cutting-edge, open-source innovation. • Thrive in the high-energy environment of a young company where openness, collaboration, risk-taking, and continuous growth are valued. • Professional development and training. • Attend conferences and working groups. • Customized workstation (macOS, Windows). • A competitive compensation package with strong benefits plan and stock options.

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