Chief Leading Expert - Next-Gen Storage Media&AI Data …, Zürich (Kreis 11)

Huawei envisions a world where technology connects people, empowers industries, and unlocks human potential.

Guided by its mission to enrich lives through communication and intelligent innovation, Huawei stands at the forefront of global digital transformation. As a leader in Information and Communications Technology (ICT), the company pioneers breakthroughs in artificial intelligence, cloud computing, and smart devices - building the intelligent foundation of a fully connected world.

Through its Carrier, Enterprise, and Consumer business groups, Huawei delivers resilient digital infrastructure, advanced cloud and AI platforms, and transformative devices that enable progress at every level. Supporting 45 of the world’s top 50 telecom operators and serving one-third of the global population across more than 170 countries, Huawei is shaping a future where connectivity becomes a powerful catalyst for opportunity and sustainable growth.

This spirit of bold innovation is embodied by Huawei Technologies Switzerland AG. From its research hubs in Zurich and Lausanne, pioneering teams push the boundaries of High-Performance Computing, Computer Architecture, Computer Vision, Robotics, Artificial Intelligence, Neuromorphic Computing, Wireless Technologies, and Networking - architecting the intelligent systems that will define tomorrow’s digital era.

As a core leader within Huawei's Zurich Storage Team, you will spearhead the research and architectural evolution of storage media systems (NAND/SSD, tape/cold media, and emerging media) optimized for the AI era. Your mission is to redefine the trade-offs between cost, performance, and scale across warm/cold data, while enabling AI training/inference pipelines to run efficiently, reliably, and economically.

You will drive innovation in Near-Data Computing (NDC) and multi-tier heterogeneous storage, shaping the backbone of future AI-ready data infrastructures.

Responsibilities:

Strategic Technical Leadership: - Define the long-term technology roadmap for warm and cold storage systems, with explicit focus on AI data lifecycle (data ingest m feature/embedding generation, vector indexing , retrieval , inference). - Lead industry insights to anticipate convergence of controller innovation and software-hardware co-design.

Architectural Innovation: - Research and develop next-generation storage architectures that reduce systemic bottlenecks in high-latency media through advanced data placement, IO scheduling, caching, and intelligent task orchestration. - Translate media constraints (latency, endurance, streaming characteristics, cost curves) into system-level architecture decisions.

AI-Driven Storage Optimization (Training + Inference + RAG): - Bridge AI workloads and storage: optimize throughput, tail latency, and reliability for large-scale training and inference. - Design storage-aware approaches for RAG pipelines (e.g., data tiering for embedding stores and vector indexes, prefetching, context/KV reuse, and“hot set” management across tiers).

Ecosystem&Collaboration: - Lead strategic technical cooperation with top-tier European universities and research institutes. - Foster an open research environment to translate breakthroughs into prototypes and product-facing technologies.

Requirements&Qualifications:

15+ years of deep expertise in storage systems (SSD/NAND, distributed/cloud storage, or cold storage systems), with a track record of leading high-impact projects and delivering measurable outcomes.

AI Infrastructure Insight: - Strong understanding of AI infrastructure needs, including LLM inference, KV cache strategies, and RAG / vector search system considerations (performance, consistency, tiering, cost).

Deep Media Expertise: - Profound expertise in at least one storage medium domain: NAND/SSD, tape/cold storage, or emerging non-volatile media. - Ability to design system-level solutions that leverage a medium's strengths while mitigating its physical limitations; working knowledge of additional media types is a plus.

System Mastery: - Expert command of storage algorithms and system techniques: data layout/arrangement, workload or application profiling, data classification/tiering, IO path optimization, scheduling, and orchestration.

Visionary Thinking: - Strong ability to reason about technology maturity cycles and translate industry trends into actionable research and product strategy.

Leadership&Communication: - Fluency in English; ability to influence cross-functional global teams and engage with senior academic/industry stakeholders.

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