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Develop and optimize RL post-training pipelines for LLMs, run experiments to improve performance and alignment, build scalable training/evaluation/data-generation systems, and collaborate with researchers and engineers on cutting-edge LLM projects while staying current with RL and post-training research.

The Project Specialist will assist the project manager in maximizing productivity, organizing schedules, reporting updates, and completing administrative tasks, ensuring quality support for Huawei Canada's projects.

The Principal Engineer will architect frameworks for serverless computing, innovate vector database storage engines, and advance vector indexing and retrieval technologies.

Conduct fundamental research in video generation, video editing, and 3D computer vision. Develop state-of-the-art AI and computer vision algorithms, create research prototypes, solve real-world problems, publish in leading conferences, integrate innovations into Huawei products, and supervise interns within collaborative R&D projects.

Conduct research and development in computer vision, deep learning, LLMs, and VLMs. Develop image and video understanding or synthesis systems, multimodal reasoning and agentic applications, and optimize models for mobile computing constraints. Responsibilities include prompt engineering, model adaptation, fine-tuning, evaluation, and reinforcement-learning-based post-training. The role also involves academic research and applying machine learning techniques to real-world problems.

Conduct research on LLM post-training, reinforcement learning, reasoning, agentic coding, and self-improving agents. Develop training methods, synthetic data, environments, evaluation systems, and scalable infrastructure for intelligent coding agents. Design experiments, implement and validate research ideas, optimize GPU workflows, analyze model behavior, and communicate findings while collaborating with research and engineering teams.

Conduct research and develop state-of-the-art speech and audio AI technologies. Responsibilities include literature reviews, algorithm implementation, data collection and analysis, deep learning and signal processing, and documenting, presenting, and publishing results while collaborating with researchers under supervision.

Conduct embodied and physical AI research, implement and deploy machine learning algorithms into internal products, collaborate with researchers, and stay current on machine learning developments. Prepare insight and technical reports. The role requires deep learning knowledge and strong Python and PyTorch coding skills; experience with large language models and robotics is preferred.

Develop and maintain software tools and infrastructure supporting machine learning and AI workflows. Build backend services, APIs, automation tools, and integrations; support large-scale experiments, evaluation, and data processing. Debug issues, improve reliability and performance, collaborate with researchers and engineers, gather user feedback, provide technical support, and write clean, tested code.

Develop C++ power system and control component models for electromagnetic transient simulation. Responsibilities include ensuring numerical stability, optimizing execution speed, benchmarking against simulation tools, documenting algorithms, creating user manuals, and building demo cases. The role requires advanced knowledge of power systems, power electronics, microgrids, numerical methods, sparse matrix decomposition, and parallel processing.