Principal Product Manager, Augmented Memory Grid

🕒 vor 12 Tagen

🇺🇸 Vereinigte Staaten – Remote

⏰ Vollzeit

🔴 Experte

✅ Produktmanager

👻 Geisterscore 10%

infoinfo

🗣️🇺🇸🇬🇧 Englisch erforderlich

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Logo of WEKA

WEKA

201 - 500 Mitarbeiter

Gegründet 2013

🤖 Künstliche Intelligenz

🏢 Unternehmen

🤝 B2B

💰 €140.000.000 Series E - WEKA im 2024-05

Artificial Intelligence • Enterprise • B2B

WEKA ist ein unternehmensorientiertes Unternehmen, das eine „AI-Native Data Platform“ bereitstellt. Die verfügbaren Materialien verweisen auf ein WEKA-Support-Portal, das für den Kundenzugang und die Kontoverwaltung genutzt wird, was darauf hinweist, dass das Unternehmen Plattformsoftware und Unterstützung für AI/Daten-Workloads anbietet, die sich an Geschäftskunden richten.

Beschreibung

• Own the AMG product roadmap, including KV-cache/prefix-cache offload, memory tiering, and integrations with inference engines and orchestration layers. • Partner with engineering to define architecture trade-offs across GPU memory, high-performance networking, and distributed storage. • Translate inference performance bottlenecks such as time-to-first-token, throughput, and context length into product requirements. • Work with enterprise customers and GPU cloud partners to gather requirements, validate benchmarks, and prioritize features that reduce cost-per-token and improve SLAs. • Partner with NVIDIA and other silicon/inference-stack partners on joint roadmap and certification work. • Define and track TTFT, throughput, and cache-hit-rate benchmarks demonstrating AMG’s value. • Support sales and field teams with technical positioning, competitive differentiation, and enterprise deal support.

🎯 Anforderungen

• Hands-on product or engineering experience with LLM inference serving, including vLLM, NVIDIA Triton/TensorRT-LLM/NIM, Ray Serve, or comparable systems • Fluency in KV-cache, prefix/context caching, quantization, and batching strategies • Working knowledge of modern production LLM serving, including context windows, multi-tenant serving, and GPU scheduling • Fundamentals of high-performance networking and distributed systems, including RDMA, GPUDirect Storage, NVMe-oF, or equivalent • Track record working directly with large enterprise accounts, including requirements gathering, production deployments, and SLAs • 10+ years of product management experience, ideally partly in infrastructure, ML platforms, or developer-facing technical products • Strong leadership skills and experience leading cross-functional teams • Ability to influence without authority • Strategic product thinking and ability to translate goals into actionable plans • Excellent communication and interpersonal skills • Ability to explain complex technical concepts to technical and non-technical stakeholders • Nice-to-have: experience at a GPU cloud, inference platform, or AI infrastructure startup • Nice-to-have: familiarity with storage systems in AI/ML pipelines • Nice-to-have: experience partnering with NVIDIA or other accelerator/silicon vendors

🏖️ Vorteile

• Equal opportunity employment • Diverse, inclusive and authentic workplace • No discrimination or harassment based on protected characteristics

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