Senior/Principal Researcher in Large Scale Systems and Applications at Huawei Technologies Co. Ltd - Singapore

Zurich, Zurich, Switzerland -

Full Time

Start Date

Immediate

Expiry Date

19 Apr, 26

Salary

0.0

Posted On

19 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Large Scale Systems, Applications Performance, Memory Systems, Interconnects, Hardware Software Co-Design, Recommender Systems, Databases, AI, Cloud Workloads, Performance Analysis, Operating Systems, Hardware Virtualization, Emerging Memory Architectures, System-Level Simulation

Industry

Telecommunications

Description

Huawei’s vision is to enrich lives through communication and intelligent innovation. As a global leader in information and communications technology (ICT), Huawei drives innovation in artificial intelligence, cloud computing, and smart device technologies. Through its Carrier, Enterprise, and Consumer business groups, the company delivers advanced Network Infrastructure, Cloud and AI Platforms, and industry-leading devices. Huawei supports 45 of the world’s top 50 telecom operators and serves one-third of the global population, with operations in over 170 countries and a workforce of more than 200,000 employees. Huawei Technologies Switzerland AG contributes to this innovation through cutting-edge research, with offices in Zurich and Lausanne focusing on High-Performance Computing, Computer Architecture, Computer Vision, Robotics, Artificial Intelligence, Neuromorphic Computing, Wireless Technologies, Networking, and related fields. We are a unique team of innovative, diverse individuals who have come together from multiple backgrounds to create advanced Computing Architectures for wireless and AI systems. The people who work here are generalists, and we complement each other. Our primary mission is driving new fundamental research and innovation to achieve breakthroughs in future computing systems. The passion for exploring uncharted territory makes us thrive. Responsibilities: · Conduct research on future large-scale systems with an emphasis on applications and their performance in relation to memory systems and interconnects. · Work with product teams in both hardware and software to identify key workloads and bottlenecks and propose optimizations and features to improve performance, utilization, and efficiency. · Identify opportunities for hardware/software co-design to accelerate modern workloads such as recommender systems, databases, AI, and cloud workloads. · Implement proof-of-concept prototypes and evaluate them on production-scale testbeds. · Prepare whitepapers and academic publications. Minimum Requirements: · PhD in computer science, computer engineering, or electrical engineering · Deep knowledge of modern enterprise applications such as recommender systems, serverless systems, and databases running on modern hardware · Knowledge of memory and networking systems (e.g., coherence protocols, virtual memory, page-table management, NUMA, CXL, RDMA) · Ability to develop and bring up applications and test on real systems · Experience with performance analysis and toolchains · Ability to evaluate existing literature to implement and expand existing state-of-the-art solutions · Papers in top-tier conferences or journals in relevant areas Preferred requirements: · Experience with operating systems (Linux kernel) · Experience with hardware virtualization · Familiarity with emerging memory architectures, memory pooling, and disaggregation · Hands-on experience in deployed cloud/enterprise systems · Practical knowledge in system-level simulation of enterprise workloads Why join us: · Collaborate with world-class scientists and engineers in an open, curiosity-driven environment; · Access to state-of-the-art technology and tools; · Opportunities for professional growth and development; · Competitive salary, and a high quality of life in Zurich, at the center of Europe; · Last but certainly not least: be part of innovative projects that make a difference.

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Responsibilities

Conduct research on future large-scale systems with a focus on applications and their performance. Collaborate with product teams to identify workloads and propose optimizations for improved performance and efficiency.