דרושים » הנדסה » Applied AI Researcher

our company, Huaweis Tel Aviv Research and Innovation Center, is looking for an experienced hands-on software architect with expertise in Cloud, AI, and Distributed Systems to join our AI-accelerated Cloud Storage group. The team designs and develops cutting-edge cloud technologies that power next-generation AI applications, optimizing performance, scalability, and efficiency.
The role involves both high-level system understanding and low-level grasp of the connection between storage and AI, to push the boundaries of cloud infrastructure for AI workloads. If you want to be part of something bigger, if you are a team player with excellent communication skills and the motivation to revolutionize AI-driven cloud technologies, youre welcome on board!
What Will You Be Doing?
Research, design, and innovate cloud-based AI acceleration technologies
Analyze AI application performance, identify bottlenecks, and optimize decision-making mechanisms
Collaborate with other engineers to develop AI optimizations, Storage backend and related POCs.
Investigate global trends in AI infrastructure and cloud computing to shape long-term architecture
Collaborate with global teams on next-generation cloud solutions for AI.

Our team at the Huawei Computing Network Innovation Lab is looking for exceptional talent to join us and lead the development of next generation data centers. We create cutting-edge technologies that synergize software and hardware in tandem to accelerate compute, storage and networking at large-scale. We aim to drive innovations and deliver software defined infrastructure and algorithms to HPC, AI/ML, and Big Data applications.
We are looking for outstanding candidates with hands-on experience in development and optimization of AI frameworks. If you are a team player with excellent communication skills and motivation to revolutionize application performance, youre welcome on board!
What will you be doing?
Work as part of an innovative research team to analyze, develop, test and deploy improvements that enhance Huaweis distributed AI framework.
Develop optimizations that leverage hardware accelerator capabilities, minimize communication overhead and improve training/inference throughput
Push the boundaries of the state of the art in LLM performance and efficiency, including model compression and quantization
Analyze, profile and optimize the latest LLM AI algorithms, and implement as production-quality software libraries for latency-critical use-cases on next-generation hardware.
Work in a distributed computing environment to optimize for both scale-up (multi-device) and scale-out (multi-node) systems
Utilize advanced concepts such as Uncertainty Quantification, Mixed Precision Computing and Model Sparsity to improve performance and enable training of very large AI models
Collaborate with partners from top universities, and open-source communities to conduct state-of-the-art research.