Job Title

Overview Huawei Canada has an immediate permanent opening for a Senior Engineer. About the team The Centre for Software Excellence Lab conducts pioneering research in software engineering, focusing on next-generation technologies. This team integrates industry best practices with cutting-edge academic research to address lifecycle software engineering challenges, including foundation model applications, software performance engineering, hyper-cluster programming, next-gen mobile OS, and cloud-native computing. This lab uniquely allows researchers to apply innovations directly to products affecting billions of customers while promoting open-source contributions, publications, conference participation, and collaborations to create a broader impact. About the job - Design and implement scalable infrastructure for various AI/LLM workloads, including but not limited to model pre-training, post training, reinforcement learning, multi modal data processing, model serving, etc. - Contribute to open-source projects and stay updated with the latest developments in AI infrastructure (e.g., Ray, vLLM, veRL) - Develop and maintain data pipelines using tools like Ray Data to handle large-scale datasets efficiently. - Optimize system performance and resource utilization across heterogeneous computing environments. - Collaborate with cross-functional teams to integrate infrastructure solutions into existing ML pipelines. - Meet top industry and academic leaders and experts around the world, collaborate with top researchers and students, consult with Engineering teams across diverse domains, publish research papers in far-reaching and impactful areas, and submit patent applications for novel inventions. About the ideal candidate - Bachelors/Master/Ph.D Degree in Computer Science, Electrical & Computer Engineering, Machine Learning, or relevant domains. - Experience with large language models (LLMs) and related infrastructure. - Solid experience with one or more of the following programming languages: Python/C++; Familiarity with software development practices (version management, build management, CI/CD, debugging and profiling). - Solid understanding in any of these areas: Machine Learning and/or Deep Learning, Large Models Training and Finetuning (e.g., NLP/CV). - Experience with mainstream model training and inference frameworks and tools (e.g., PyTorch, HuggingFace Transformer&Accelerate, DeepSpeed, Megatron, veRL). - Experience in using frameworks and tools of any of the aforementioned areas (e.g., Spark, Flink, Ray for Distributed Computing, Docker, K8S for Cloud-Native app/framework development). - Ability to evaluate, apply, and mature published research to real-world problems on prototype systems and have an inquisitive mindset, proven research and communication. #J-18808-Ljbffr