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Jobverse.io

Researcher - AI Computing System

Vancouver, BC, Canada

Contract

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Job details

Job type: Contract
Apply by: Nov 28, 2026
Posting language: English
Posted: Oct 29, 2026

Original job description

Huawei Canada is hiring a Researcher to advance performance, efficiency, and usability of AI systems on its Ascend platform. The role develops optimization solutions for AI training and inference, improves computing systems and training clusters, and contributes to large-model acceleration and AI computing architecture research.

Responsibilities

Aiming at key industry AI application scenarios such as large model training and inference, this role focuses on advancing performance, efficiency, and usability of AI systems on the Ascend platform. The work involves low-precision training, multimodal optimization, reinforcement learning, and training resource optimization to address system bottlenecks and deliver next-generation AI capabilities
Responsible for design and development of optimization solutions for AI training and inference systems, with a focus on FP8 optimization, RL-driven training agents, multimodal reinforcement learning or next-generation multi-modal understanding & generation
Combine AI algorithm requirements with system-level architectural optimization in computing, I/O, scheduling, and precision control to improve performance
Build stable, efficient AI training clusters, leveraging dynamic cluster configuration and precision control to ensure scalability and reliability
Develop software frameworks, operator libraries, acceleration libraries, and system-level optimizations for NPU platforms to accelerate large-model AI training
Drive innovation in optimizing large-model training and inference with low-precision training, parallel strategy tuning, and reinforcement learning
Grasp the latest research progress and technological trends in AI computing cluster architecture design, training acceleration, and inference acceleration across academia and industry to strengthen the competitiveness of AI computing cluster systems

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More about this job

Responsibilities

Design and develop system-level optimization solutions for AI training and inference on Huawei's Ascend platform, including low-precision training, reinforcement learning, multimodal workloads, and large-model acceleration. Improve computing architecture, training clusters, software frameworks, and acceleration libraries to increase performance, efficiency, scalability, and reliability.

Requirements

The role calls for expertise in AI training and inference optimization, computing systems, and large-model acceleration, including low-precision methods, reinforcement learning, and multimodal workloads. It also requires the ability to combine AI algorithm needs with system-level optimization and stay current with research in cluster architecture and training and inference acceleration.

Skills

AI Training Optimization
AI Inference Optimization
FP8 Optimization
Low-Precision Training
Reinforcement Learning
Multimodal Optimization
AI Computing Architecture
Computing Systems Optimization
Training Cluster Optimization
Parallel Strategy Tuning
NPU Platforms
Operator Libraries
Acceleration Libraries
Cluster Configuration
Precision Control
Large-Model Acceleration

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Keywords

Huawei Ascend
AI Computing Systems
AI Training
AI Inference
FP8
Low-Precision Training
Multimodal Optimization
Multimodal Reinforcement Learning
Reinforcement Learning
Large-Model Training
Large-Model Inference
AI Computing Architecture
Computing Optimization
I/O Optimization
Scheduling
Precision Control
Training Clusters
Dynamic Cluster Configuration
NPU Platforms
Software Frameworks
Operator Libraries
Acceleration Libraries
Parallel Strategy Tuning
Training Acceleration
Inference Acceleration
Cluster Architecture

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