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Training manager • scarborough on
Principal Architect – Hardware Efficient AI Foundation Model Training
Huawei Technologies Canada Co., Ltd.Markham, Ontario, CAAccount Manager
Crystal Claire Cosmetics Inc.Markham, ONMarketing manager
Altec Global Capital Inc.North York, ON, CanadaPrincipal Engineer - Gen AI training and inferencing
Advanced Micro Devices, IncMARKHAM, Ontario, Canada- New!
Environmental Manager
AECOMMarkham, Ontario, CanadaSenior Training Specialist
Randstad CanadaNorth York, Ontario, CABranch Manager
NedcoMarkham, ON, CABusiness Manager (Financial Services Manager)
Serpa Automotive GroupScarborough, Ontario, CanadaAssistant Manager
Tim HortonsMarkham, ONIT MANAGER
Kariera.Recruitment Services GreeceMessini- Promoted
Payroll Manager
Vaco by HighspringNewtonbrook, Ontario, CanadaRestaurant manager
DICKEYS BARBEQUE PITMarkham, ON, CanadaCondominium Manager
FirstService ResidentialPickering, ON, CAManager, Meat
SobeysPickering, ON, CA- Burnaby, BC (from $ 78,000 to $ 171,503 year)
- Sydney, NS (from $ 91,091 to $ 166,117 year)
- Cambridge, ON (from $ 159,412 to $ 165,898 year)
- Victoria, BC (from $ 58,755 to $ 165,005 year)
- Windsor, ON (from $ 57,907 to $ 164,751 year)
- Guelph, ON (from $ 159,271 to $ 164,620 year)
- Surrey, BC (from $ 70,258 to $ 164,496 year)
- St. Catharines, ON (from $ 59,955 to $ 164,483 year)
- London, ON (from $ 94,088 to $ 164,438 year)
- Halifax, NS (from $ 59,004 to $ 164,208 year)
Principal Architect – Hardware Efficient AI Foundation Model Training
Huawei Technologies Canada Co., Ltd.Markham, Ontario, CA- Full-time
- Permanent
Job description
Huawei Canada has an immediate permanent opening for a Principal Architect.
About the team:
The Computing Data Application Acceleration Lab aims to create a leading global data analytics platform organized into three specialized teams using innovative programming technologies. This team focuses on full-stack innovations, including software-hardware co-design and optimizing data efficiency at both the storage and runtime layers. This team also develops next-generation GPU architecture for gaming, cloud rendering, VR/AR, and Metaverse applications.
One of the goals of this lab are to enhance algorithm performance and training efficiency across industries, fostering long-term competitiveness.
About the job:
Collaborate with internal and external organizations to lead the design of foundational model architecture for LLM/Code/Multimodal subfields by breakthroughs in post-training and continual training. Develop a foundational model with state-of-the-art performance and hardware efficiency, and establish industry impact.
Propose the technical requirements for large-scale distributed training and inference infrastructures such as parallelization and operator fusion, analyze the computational characteristics of typical architectures, and ensure the accuracy and advancement of AI hardware & infrastructure evolution.
Job requirements
About the ideal candidate:
Experience in training and optimizing cutting-edge AI models/applications, especially in training and deploying AI models at a scale of 10B+ parameters.
Proficiency in the latest AI architecture (such as long-sequence, reinforcement learning, multimodal, and agents). Deep understanding of AI algorithm mechanisms.
Solid command of the underlying implementation of AI frameworks (such as PyTorch, vLLM, and SGLang), and mainstream distributed training and inference techniques.
Familiarity with AI chip architecture (such as GPU, NPU, and TPU). Understanding of memory hierarchy and interconnect technologies is an asset.
PhD preferred in AI architecture, computer architecture, or related fields.
Solid publication records in the field of AI systems or chip design are an asset.