Note: The job is a remote job and is open to candidates in USA. WEKA is seeking a Product Manager to lead the roadmap and go-to-market strategy for Augmented Memory Grid (AMG), part of its NeuralMesh platform. The role focuses on AI inference infrastructure, high-performance networking, and enterprise storage, partnering with engineering, GPU and inference-stack vendors, cloud partners, and enterprise customers to define product requirements, benchmarks, and market positioning.
Responsibilities
- Own the AMG product roadmap: KV-cache/prefix-cache offload, memory tiering, and integration with inference engines and orchestration layers (vLLM, NVIDIA Triton/TensorRT-LLM/NIM, Kubernetes-based serving)
- Partner with engineering to define architecture trade-offs across GPU memory, networking (RDMA, GPUDirect, NVMe-oF), and distributed storage — translating inference performance bottlenecks (time-to-first-token, throughput, context length) into product requirements
- Work directly with enterprise customers and GPU cloud partners: Nebius, CoreWeave, TogetherAI, etc., running production inference workloads to gather requirements, validate benchmarks, and prioritize features that reduce cost-per-token and improve SLAs at scale
- Partner with NVIDIA and other silicon/inference-stack partners on joint roadmap and certification work
- Define and track benchmarks (TTFT, throughput, cache hit rate) that demonstrate AMG's value versus standard GPU-memory-only inference
- Support sales and field teams with technical positioning, competitive differentiation, and enterprise deal support
Skills
- Strong leadership skills with a history of successfully leading cross-functional teams. Product Managers are expected to inspire and motivate team members to achieve ambitious goals while maintaining a collaborative and positive working environment. You understand how to influence without authority, and your recall of meaningful details supports verbal and written agility
- You are a strategic thinker who can develop and execute product strategies that align with market trends and customer needs, as well as think critically about existing strategies. You have a proven ability to translate strategic goals into actionable plans and deliver results
- You have excellent communication and interpersonal skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders. You are comfortable presenting product strategies and roadmaps to internal teams and external customers
- Hands-on product or engineering experience with LLM inference serving — vLLM, NVIDIA Triton/TensorRT-LLM/NIM, Ray Serve, or comparable — and fluency in concepts like KV-cache, prefix/context caching, quantization, and batching strategies
- Working knowledge of how modern LLMs are served in production (context windows, multi-tenant serving, GPU scheduling) well enough to translate model-level constraints into infrastructure requirements
- Comfort with the fundamentals of high-performance networking and distributed systems — RDMA, GPUDirect Storage, NVMe-oF, or equivalent — and how they affect inference performance
- Track record working directly with large enterprise accounts — requirements gathering, production deployments, SLAs — not solely self-serve/PLG products
- 10+ years of product management experience, ideally with some portion in infrastructure, ML platforms, or developer-facing technical products
- Prior experience at a GPU cloud, inference platform, or AI infrastructure startup
- Familiarity with storage systems (parallel/distributed file systems, object storage) in AI/ML pipelines
- Experience partnering directly with NVIDIA or other accelerator/silicon vendors
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