Lab Director – AI Infrastructure for Large-scale Models

We are seeking a visionary and technically distinguished Lab Director to lead the Huawei Paris Distributed & Parallel Computing Lab. This role is central to our mission: driving innovation and breakthroughs in large-scale AI infrastructure, and delivering high-quality technologies into real-world applications. You will serve as the technical leader of the lab, guiding both strategy and execution in one of Huawei's most advanced AI research directions.
Key Responsibilities
• Strategic Leadership: Define and lead the lab’s R&D strategy in AI infrastructure for large-scale model training and inference. Identify core research problems and long-term innovation goals.
• Technology Innovation & Delivery: Lead the team in cutting-edge research and engineering in areas such as distributed parallel computing, automatic parallelization, graph scheduling, and numerical computing. Ensure high-quality technology delivery and practical integration.
• Team Leadership: Build, manage, and mentor a top-tier team of researchers and engineers. Foster a high-performance, innovation-driven culture.
• Cross-Team Collaboration: Collaborate closely with Huawei’s headquarters and global research teams to align efforts and achieve integrated technology deployment.
• External Influence: Represent Huawei in global academic and industrial communities. Participate in or lead top-tier conferences (e.g., NeurIPS, ICLR, MLSys, OSDI, SC) and engage in standardization or open-source initiatives.
Focus Areas
Our lab focuses on AI infrastructure technologies supporting large model training and inference, including but not limited to:
• Distributed Parallelism: Automatic parallelization, pipeline parallelism, tensor parallelism, and communication optimization
• Execution Graph Optimization: Dynamic/static computation graph scheduling and compiler-level graph optimization
• Numerical Computation: Sparse training, mixed precision, low-rank decomposition, dimensionality reduction
• Heterogeneous Computing
Requirements:
Required:
• Strong technical expertise in one or more of the following areas: large-scale model systems, AI infrastructure, distributed systems, compiler design, or numerical computing
• Proven track record in leading high-impact research or engineering teams (10+ members)
• Experience in designing or delivering scalable AI platforms or model systems in industry or academia
• Background in a world-class tech company, startup, or research institute
• Fluent in English (working proficiency); French is a plus
Preferred:
• Publications in top-tier conferences/journals (e.g., NeurIPS, ICML, ICLR, OSDI, SOSP, MLSys, TPDS)
• Leadership experience in open-source or industrial LLM systems
• Familiarity with Huawei Ascend / Atlas architecture or other mainstream AI hardware systems